{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "960ceacb-3c3f-484c-95b9-172bd009b1a4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is a generic code for drawing a state's Home Districts for neutral map estimation\n",
      "In this code, we use the term 'tract' generically to refer the base building block, usually vtd's\n"
     ]
    }
   ],
   "source": [
    "#  THIS IS THE PRIMARY VERSION TO USE FOR ALL STATES  #See MO for orig 2/10/24.  This one from NC 4/19/24\n",
    "print(\"This is a generic code for drawing a state's Home Districts for neutral map estimation\") #Jan'24\n",
    "print(\"In this code, we use the term 'tract' generically to refer the base building block, usually vtd's\")\n",
    "import shapely\n",
    "from shapely.geometry import Point, LineString, Polygon\n",
    "from shapely.ops import nearest_points, transform\n",
    "from shapely.affinity import translate, scale\n",
    "import geopandas as gpd\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from numpy import random\n",
    "from scipy.stats import norm\n",
    "from scipy.optimize import minimize, minimize_scalar\n",
    "import math\n",
    "import time\n",
    "import ast\n",
    "# from HDmethods import *   #I want to implement this, but my HDmethods require shapely functions\n",
    "# see https://stackoverflow.com/questions/66877728/proper-way-to-use-import-when-calling-external-function for a future workaround\n",
    "\n",
    "dummyPoly = Polygon([(0,0),(0,1),(1,1)])\n",
    "#handy function for plotting Polygon or multiPolygon tracts and precincts\n",
    "def plotPoly(inputPoly,LW=1):\n",
    "    dummyPoly = Polygon([(0,0),(0,1),(1,1)])\n",
    "    if inputPoly.geom_type == dummyPoly.geom_type:\n",
    "        x,y = inputPoly.exterior.xy\n",
    "        plt.plot(x,y,lw=LW)\n",
    "    else:\n",
    "        for geom in inputPoly.geoms:\n",
    "            if geom.area > 0:  #to avoid error with LineString geom parts\n",
    "                x,y = geom.exterior.xy\n",
    "                plt.plot(x,y,lw=LW)  \n",
    "def plotCenter(t,geom,FONTSIZE=10):\n",
    "    plt.text(geom.centroid.x,geom.centroid.y,t,ha='center',fontsize=FONTSIZE)\n",
    "    \n",
    "def r3(number):\n",
    "    result = round(number,3)\n",
    "    return result\n",
    "\n",
    "def r5(number):\n",
    "    result = round(number,5)\n",
    "    return result\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2ab4a3d5-f4e7-4aec-b81c-0e786cd35b57",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def getWeightedAvgAndSD(LIST, WEIGHTS):  #from IN\n",
    "    nWeights = len(WEIGHTS)\n",
    "    normWeights = [WEIGHTS[i] / np.sum(WEIGHTS) for i in range(nWeights) ]\n",
    "    AVG = 0.\n",
    "    for i, value in enumerate(LIST):\n",
    "        AVG += normWeights[i] * value\n",
    "    sumVar = 0.\n",
    "    for i, value in enumerate(LIST):\n",
    "        sumVar += normWeights[i] * (value - AVG)**2\n",
    "    SD = sumVar ** 0.5     #don't need to normalize again since weights were normalized\n",
    "    return AVG, SD\n",
    "\n",
    "def squish(shapeList, cutLINE, farLINE, newFarLINE):\n",
    "    \"\"\"\n",
    "    This method compresses a list of shapes lying between the cutLINE and the farLINE)\n",
    "    such that the Polygons now lie between the cutLINE and the newFarLINE, which is closer to the cutLINE\n",
    "    Used to compress state outcroppings into a more compact state representation.\n",
    "     (I tried doing this point by point (see #'s), but this overdistorted geometries.)\n",
    "      (#This was a manual alternative to shapely.affinity.scale and .translate operations)\n",
    "       So instead, we run this AFTER established untransformed map topology, and \n",
    "        we simply scale and translate each unit.  This loses true connectivity.\n",
    "        Scaling is all lengths scale by compression of distance\n",
    "    The cut, far, and newFar LineString segments are preferably parallel\n",
    "    The method returns the modified shapes of all pollys\n",
    "    \"\"\"\n",
    "    if cutLINE.intersects(farLINE) or cutLINE.intersects(newFarLINE):\n",
    "        print(\"cutLine,farLine, newFarLine were\",cutLINE, farLINE, newFarLINE)\n",
    "        raise Exception(\"ERROR: the proposed cutLine intersects the current or proposed far line\")\n",
    "    newPollys = list()\n",
    "    for polly in shapeList:\n",
    "        pollyCP = polly.centroid\n",
    "        cutPt =     nearest_points(cutLINE,   pollyCP)[0]\n",
    "        farPt =     nearest_points(farLINE,   pollyCP)[0]\n",
    "        newFarPt =  nearest_points(newFarLINE,pollyCP)[0]\n",
    "        curr_cutX, curr_cutY =            pollyCP.x - cutPt.x, pollyCP.y -  cutPt.y\n",
    "        currFar_CutX , currFar_CutY  =    farPt.x - cutPt.x, farPt.y   -  cutPt.y\n",
    "        new_currFarX, new_currFarY =      newFarPt.x - farPt.x, newFarPt.y - farPt.y\n",
    "        newFar_CutX,  newFar_CutY =       newFarPt.x - cutPt.x, newFarPt.y   -  cutPt.y\n",
    "        distanceRatio = newFarPt.distance(cutPt)/farPt.distance(cutPt) #scale area ^length^2\n",
    "        XOFF,YOFF = 0., 0.\n",
    "        XFACT, YFACT = 1., 1.  #default = no stretch\n",
    "        # basic equation: (new-cut)/(curr-cut) = (newFar-cut)/(currFar - cut)\n",
    "        #  or: (new-curr)  = (curr-cut)*(newFar-currFar)/(currFar - cut)   # -1 to both sides\n",
    "        if currFar_CutX != 0:\n",
    "            XOFF =  curr_cutX * new_currFarX / currFar_CutX\n",
    "            XFACT =              newFar_CutX / currFar_CutX\n",
    "        if currFar_CutY != 0:\n",
    "            YOFF =  curr_cutY * new_currFarY / currFar_CutY\n",
    "            YFACT =              newFar_CutY / currFar_CutY\n",
    "        newPolly = translate(polly,xoff=XOFF,yoff=YOFF)\n",
    "        newPolly = scale(newPolly, xfact=XFACT, yfact=YFACT, origin='centroid')\n",
    "        newPollys.append( newPolly )       \n",
    "    return newPollys\n",
    "\n",
    "def getHDcp(TRACTCP,TRACTPOP, TRACTLIST, SPLITTRACTNO = -777,SPLITTRACTUSE = 1.):  #population centerpoint of a Home District or county (cluster)\n",
    "    cpx, cpy, sumPop = 0.,0., 0.\n",
    "    for tt in TRACTLIST:\n",
    "        USE = 1.\n",
    "        if tt ==    SPLITTRACTNO:\n",
    "            USE =   SPLITTRACTUSE\n",
    "        sumPop += USE*TRACTPOP[tt]\n",
    "        cpx +=    USE*TRACTPOP[tt] * TRACTCP[tt].x\n",
    "        cpy +=    USE*TRACTPOP[tt] * TRACTCP[tt].y\n",
    "    HDCP_ = Point(cpx/sumPop, cpy/sumPop)\n",
    "    return HDCP_\n",
    "\n",
    "#  The below four methods are TO SNAP to HD SHAPES without any solving / iteration\n",
    "def buildWedge(CP,STARTANGLE, ENDANGLE, RR,XSCALE=1.0):\n",
    "    \"\"\"\n",
    "    This method creates triangular wedges from a centerpoint, wedge start and end angles, and wedge radius.\n",
    "    The optional xScale parameter is the ratio of longitude to latitude lengths scales (<<1 for far from equator)\n",
    "    It passes back a SINGLE wedge polygon\n",
    "    \"\"\"\n",
    "    A0 = STARTANGLE\n",
    "    A1 = ENDANGLE\n",
    "    PT1 = Point(CP.x + RR/XSCALE*math.cos(A0),  CP.y + RR*math.sin(A0) )\n",
    "    PT2 = Point(CP.x + RR/XSCALE*math.cos(A1),  CP.y + RR*math.sin(A1) )\n",
    "    WEDGEPOLY = Polygon( [CP,PT1, PT2 ])\n",
    "    return WEDGEPOLY\n",
    "\n",
    "def buildPoly(CP, RADII, ANGLES, XSCALE = 1.0):  #reconstructs a 4-tri polygon from four HD wedges emanating from the centerpoint\n",
    "    Pt = [Point(0,0)]*12                      #xScale has same meaning as in buildWedge\n",
    "    for nW in range(4): \n",
    "        ccwAngle = ANGLES[nW]  #these two are the angles at start and end of nth wedge\n",
    "        cwAngle =  ANGLES[ int((nW+1)%4) ]  \n",
    "        Pt[nW*2] =   Point(CP.x + RADII[nW]/XSCALE*math.cos(ccwAngle), CP.y + RADII[nW]*math.sin(ccwAngle) )\n",
    "        Pt[nW*2+1] = Point(CP.x + RADII[nW]/XSCALE*math.cos( cwAngle), CP.y + RADII[nW]*math.sin( cwAngle) )        \n",
    "    POLLY = Polygon([Pt[0],Pt[1],Pt[2],Pt[3],Pt[4],Pt[5],Pt[6],Pt[7] ])\n",
    "    return POLLY\n",
    "\n",
    "def buildArcPoly(CP, RADII, ANGLES, XSCALE = 1.0):  #reconstructs a fuller polygon from four HD wedges emanating from the centerpoint\n",
    "    twoPi = 2. * 3.1415926   #xScale has same meaning as in buildWedge\n",
    "    POINTS = list()                   \n",
    "    for nW in range(4): \n",
    "        ccwAngle = ANGLES[nW] % twoPi                 #these two are the angles at start and end of nth wedge\n",
    "        cwAngle =  ANGLES[ int((nW+1)%4) ] % twoPi \n",
    "        midAngle = [0.75*ccwAngle + 0.25*cwAngle , 0.25*ccwAngle + 0.75*cwAngle ]  #avoid s sampling cone center for wide angles\n",
    "        if abs (ccwAngle - cwAngle) > 3.1415926 :  #angles straddle angle=0\n",
    "            midAngle = [0.75*(ccwAngle - twoPi) + 0.25*cwAngle , 0.25*(ccwAngle -twoPi) + 0.75*cwAngle ]\n",
    "        angList = [ccwAngle] + midAngle + [cwAngle]\n",
    "        for ang in angList:\n",
    "            POINTS.append(Point(CP.x + RADII[nW]/XSCALE*math.cos(ang), CP.y + RADII[nW]*math.sin(ang) ) )\n",
    "                          \n",
    "    POLLY = Polygon(POINTS)\n",
    "    return POLLY\n",
    "\n",
    "def getPolyPop(POLLY, TRACTCP, TRACTPOP, CANDIDATELIST ):  #simple capture of pop points contained by a polygon\n",
    "    WPOP, WLIST = 0., list()\n",
    "    for tt in CANDIDATELIST:\n",
    "        if POLLY.contains(TRACTCP[tt]):\n",
    "            WPOP += TRACTPOP[tt]\n",
    "            WLIST.append(tt)\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def getNonCPP(POLLY, HC, TRACTCP, TRACTPOP, COUNTYGEOM, COUNTYPOP, COUNTYTRACTLIST, NEIGHBORCOUNTYLIST) : #nonCounty wedgePop\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by a POLLY polygon for counties contiguous with the Home County (no hop-overs)\n",
    "    , EXCLUDING the home county for the centerpoint of the wedge.  This should be more efficient than probing every unit in the map\n",
    "    After each county is checked, it goes into the checked list so we don't re-check, then we recursively probe county neighbors\n",
    "    \"\"\"\n",
    "    WPOP, WLIST = 0., list()\n",
    "    checkedClist = [HC]   #dynamic list of counties we've already checked.  We probed the home county in getPolyPop\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "                        if POLLY.contains(COUNTYGEOM[cc]):\n",
    "                            WPOP += COUNTYPOP[cc]\n",
    "                            WLIST += COUNTYTRACTLIST[cc]\n",
    "                        else:\n",
    "                            for tt in COUNTYTRACTLIST[cc]:\n",
    "                                if POLLY.contains(TRACTCP[tt]):\n",
    "                                    WPOP += TRACTPOP[tt]\n",
    "                                    WLIST.append(tt)\n",
    "        #below is temp debug\n",
    "        #print(len(intersectedClist),WPOP, len(WLIST),\"counties probed, pop, len(tractList)\")\n",
    "        latestClist = newClist.copy()\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def getNonHCunits(POLLY, HC, UNITLIST, UNITCP, UNITPOP, ALLFUSEDCOUNTIES, AREAFRAC, COUNTYGEOM, \n",
    "                  NEIGHBORCOUNTYLIST, COUNTYUNITLIST):\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by a POLLY polygon for counties contiguous with the Home County (no hop-overs)\n",
    "    , EXCLUDING the home county.  This should be more efficient than probing every unit in the map\n",
    "    After each county is checked, it goes into the checked list so we don't re-check, then we recursively probe county neighbors\n",
    "    \"unit counties\" are added as whole units if a sufficient area fraction is captured.  For non-unitCs, we probe each component vtd / tract\n",
    "    \"\"\"\n",
    "    UPOP, ULIST = 0., list()\n",
    "    checkedClist = [HC]   #dynamic list of counties we've already checked.  We probed the home county before we called this method\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        #1/9/24 - DO WE NEED TO MODIFY THE ORDER BELOW TO AVOID CREATING HOLES AND ENCLAVES ??  #\n",
    "        \n",
    "        for c in latestClist:\n",
    "            for cc in list( set(NEIGHBORCOUNTYLIST[c]).difference(set(ALLFUSEDCOUNTIES)) ):\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        if cc+0.5 in UNITLIST:\n",
    "                            if POLLY.intersection(COUNTYGEOM[cc]).area >=  AREAFRAC[cc] * COUNTYGEOM[cc].area :\n",
    "                                intersectedClist.append(cc)   #for unit counties, intersections count only if they capture sufficient area\n",
    "                                newClist.append(cc)\n",
    "                                UPOP += UNITPOP[UNITLIST.index(cc+0.5)]\n",
    "                                ULIST.append( UNITLIST.index(cc+0.5) )\n",
    "                        else:                           \n",
    "                            intersectedClist.append(cc)\n",
    "                            newClist.append(cc)\n",
    "                            if POLLY.contains(COUNTYGEOM[cc]):\n",
    "                                unitsToAdd = COUNTYUNITLIST[cc]\n",
    "                                UPOP += np.sum(  [ UNITPOP[uu] for uu in unitsToAdd ]  )\n",
    "                                ULIST += unitsToAdd\n",
    "                            else:\n",
    "                                for uu in COUNTYUNITLIST[cc]:\n",
    "                                    if POLLY.contains(UNITCP[uu]):\n",
    "                                        UPOP += UNITPOP[uu]\n",
    "                                        ULIST.append(uu)\n",
    "        latestClist = newClist.copy()\n",
    "        \n",
    "    return UPOP, ULIST\n",
    "\n",
    "def clusterSwell(CP_, CCBgeom, CCBpop, allUnits, unitCP, unitPop, unitNbrs, borderUnits, TGTPOP):\n",
    "    \"\"\"\n",
    "    This method grows a Home District by \"swelling\" from a corner county cluster.  First, we add the full cluster,\n",
    "     then we add closest neighbor units to the home district centerpoint CP_ until we reach the TGTPOP\n",
    "     new for MN 4/7/24 - don't enforce contiguity here -- too slow -- fix in cleanup stage instead\n",
    "     \"\"\"\n",
    "    hd_CCBdist = [CP_.distance(geo) for geo in CCBgeom]\n",
    "    CCBno = hd_CCBdist.index(np.min(hd_CCBdist))  #ID's the closest cluster to this HD center.  Should contain the HD, but rarely will not\n",
    "    unitNo = allUnits.index(CCBno+0.25)\n",
    "    newList, prevList, addedList, addedPop = [unitNo], [unitNo], [unitNo], unitPop[unitNo]  #seed with the cluster pop and unit\n",
    "    while addedPop < 0.99 * TGTPOP and len(newList) > 0:\n",
    "        tryList = getAdjoiners(addedList,unitNbrs)\n",
    "        tryDist = [ CP_.distance(unitCP[UU]) for UU in tryList ]\n",
    "        idx = np.argsort(tryDist)\n",
    "        idxNo, newList = 0, list()\n",
    "        haveNotAdded = True\n",
    "        while idxNo < len(tryList) and haveNotAdded:\n",
    "            UU = tryList[idx[idxNo]]\n",
    "            if unitPop[UU] + addedPop < 1.01 * TGTPOP :  #and wontEnclave(UU, addedList, unitNbrs, borderUnits) :  #we'll post-fix contig'y\n",
    "                newList.append(UU)\n",
    "                addedList.append(UU)\n",
    "                addedPop += unitPop[UU]\n",
    "                haveNotAdded = False\n",
    "            idxNo +=1\n",
    "        prevList = newList.copy()\n",
    "        \n",
    "    return addedPop, addedList\n",
    "            \n",
    "def getFakeHC(HDPOLLY, HC, CCBlist, countyGeom, MAP) :\n",
    "    \"\"\"\n",
    "    This method is for setting a fake home county for counties in corner clusters, so that county neighbors can be found budding from the \"home county\"\n",
    "    We pick the county in the cluster closest to the map center and intersecting the HDpoly.  This will be an active county on the cluster boundary   \n",
    "    \"\"\"\n",
    "    MAPcenter = MAP.centroid\n",
    "    for L in CCBlist:\n",
    "        if HC in L:\n",
    "            distList, cList = list(), list()\n",
    "            for C in L:\n",
    "                if HDPOLLY.intersects(countyGeom[C]):\n",
    "                    distList.append(countyGeom[C].distance(MAPcenter))\n",
    "                    cList.append(C)\n",
    "    fakeHC = cList[distList.index(np.min(distList)) ]\n",
    "    return fakeHC\n",
    "\n",
    "def getLongDist(CP1, CP2, xScale = 1.0): #distance between two points with EW distance scaled down by latitude\n",
    "    #LAT = MAP.centroid.y\n",
    "    #xScale = (1. - 1.089* abs(LAT/90)**1.9)\n",
    "    dist = ( xScale*xScale * (CP1.x - CP2.x)*(CP1.x - CP2.x)  +  (CP1.y - CP2.y)*(CP1.y - CP2.y) ) **0.5 \n",
    "    return dist\n",
    "\n",
    "# THESE ARE THE METHODS USED IN SOLVING HD SHAPES\n",
    "def buildWedge(CP,STARTANGLE, ENDANGLE, RR,XSCALE=1.0):\n",
    "    \"\"\"\n",
    "    This method creates triangular wedges from a centerpoint, wedge start and end angles, and wedge radius.\n",
    "    It passes back a SINGLE wedge polygon\n",
    "    \"\"\"\n",
    "    A0 = STARTANGLE\n",
    "    A1 = ENDANGLE\n",
    "    PT1 = Point(CP.x + RR/XSCALE*math.cos(A0),  CP.y + RR*math.sin(A0) )\n",
    "    PT2 = Point(CP.x + RR/XSCALE*math.cos(A1),  CP.y + RR*math.sin(A1) )\n",
    "    WEDGEPOLY = Polygon( [CP,PT1, PT2 ])\n",
    "    return WEDGEPOLY\n",
    "\n",
    "def getCountyWP(T, WEDGEPOLY, TRACTCP, TRACTPOP, CANDIDATELIST ):  #simple capture of pop points in a wedge excluding a point\n",
    "        WPOP, WLIST = 0., list()\n",
    "        for tt in CANDIDATELIST:\n",
    "            if tt != T and WEDGEPOLY.contains(TRACTCP[tt]):\n",
    "                WPOP += TRACTPOP[tt]\n",
    "                WLIST.append(tt)\n",
    "        return WPOP, WLIST\n",
    "\n",
    "def getNonCWP(WEDGEPOLY, HC, TRACTCP, TRACTPOP, COUNTYGEOM, COUNTYPOP, COUNTYTRACTLIST, NEIGHBORCOUNTYLIST) : #nonCounty wedgePop\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by an infinite polygonal wedge for counties contiguous with the Home County (no hop-overs)\n",
    "    , EXCLUDING the home county for the centerpoint of the wedge.  This should be more efficient than going tract-by-tract\n",
    "    After each county is checked, it goes into the checked list so we don't re-check.  Next round = nonchecked neighbors of current round\n",
    "    \"\"\"\n",
    "    WPOP, WLIST = 0., list()\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if WEDGEPOLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "                        if WEDGEPOLY.contains(COUNTYGEOM[cc]):\n",
    "                            WPOP += COUNTYPOP[cc]\n",
    "                            WLIST += COUNTYTRACTLIST[cc]\n",
    "                        else:\n",
    "                            for tt in COUNTYTRACTLIST[cc]:\n",
    "                                if WEDGEPOLY.contains(TRACTCP[tt]):\n",
    "                                    WPOP += TRACTPOP[tt]\n",
    "                                    WLIST.append(tt)\n",
    "        #below is temp debug\n",
    "        #print(len(intersectedClist),WPOP, len(WLIST),\"counties probed, pop, len(tractList)\")\n",
    "        latestClist = newClist.copy()\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def isIncludedA(STARTa, ENDa, TESTa): #determines if a test angle is between a start and end angle (True)\n",
    "    \"\"\"\n",
    "    The start angle must be less than the end angle when placed on the [0, 2 pi] interval  (ccw convention)\n",
    "    \"\"\"\n",
    "    pi = 3.141592653\n",
    "    STARTa, ENDa, TESTa = STARTa % (2.*pi), ENDa % (2.*pi), TESTa % (2.*pi)  #place on the 2pi interval\n",
    "    isIncludedA = False\n",
    "    if STARTa  > ENDa :  #included angle straddles east\n",
    "        if   TESTa  >= STARTa or TESTa < ENDa :  #near-east between the two\n",
    "            isIncludedA = True\n",
    "    else:\n",
    "        if TESTa >= STARTa and TESTa < ENDa :  #normal case\n",
    "            isIncludedA = True\n",
    "    return isIncludedA\n",
    "\n",
    "def getNonCWP_c(STARTANGL, ENDANGL, HC, TRACTCP,TRACTPOP,COUNTYGEOM,COUNTYPOP,COUNTYTRACTLIST,\n",
    "                                    NEIGHBORCOUNTYLIST, UUDIST, UUANGLE, WEDGEPOLY) :\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by a polygonal wedge for counties contiguous with the Home County (no hop-overs),\n",
    "    EXCLUDING the home county for the centerpoint of the wedge.  This should be more efficient than going tract-by-tract\n",
    "    After each county is checked, it goes into the checked list so we don't re-check.  Next round = nonchecked neighbors of current round\n",
    "    Unlike its getNonCWP vanilla parent, this one uses angles rather than infinite wedges for units (still wedges for counties)\n",
    "    \"\"\"\n",
    "    WPOP, WLIST = 0., list()\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if WEDGEPOLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "                        if WEDGEPOLY.contains(COUNTYGEOM[cc]):\n",
    "                            WPOP += COUNTYPOP[cc]\n",
    "                            WLIST += COUNTYTRACTLIST[cc]\n",
    "                        else:\n",
    "                            for tt in COUNTYTRACTLIST[cc]:\n",
    "                                if isIncludedA(STARTANGL, ENDANGL, UUANGLE[tt]): #WEDGEPOLY.contains(TRACTCP[tt]):\n",
    "                                    WPOP += TRACTPOP[tt]\n",
    "                                    WLIST.append(tt)\n",
    "        #below is temp debug\n",
    "        #print(len(intersectedClist),WPOP, len(WLIST),\"counties probed, pop, len(tractList)\")\n",
    "        latestClist = newClist.copy()\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def getExitAngle(CP,WEDGEPOLY, MAP, A0, A1):\n",
    "    \"\"\"\n",
    "    This code determines the orientation angle from a CenterPoint to the intersection of a wedge with an exterior boundary\n",
    "    If an intersection is not found, we just take the average angle of the wedge start/stop angles A0, A1 as this orientation angle\n",
    "    MAP must be a single polygon for this to work in the revised code (tho could run thru all polygons in MAP if a multipolygon)\n",
    "    \"\"\"\n",
    "    EXITANGLE = 0.5* (A0 + A1) #this will be the angle from the x-axis to the exit beeline\n",
    "    if WEDGEPOLY.intersects(MAP.exterior):\n",
    "        edgeLine = WEDGEPOLY.intersection(MAP.exterior) #true state boundary line where wedge crossed it\n",
    "        closePoint = nearest_points(edgeLine,CP)[0]\n",
    "        dx = closePoint.x - CP.x       #this and below lines were indented in original code***\n",
    "        dy = closePoint.y - CP.y\n",
    "        EXITANGLE =  pi/2. * np.sign(dy)  #default in case dx=0\n",
    "        if (dx != 0. ):\n",
    "            EXITANGLE = math.atan(dy/dx) + random.uniform(-0.01,0.01) #add wiggle to avoid exact NESW orientation in gridded states\n",
    "            if dx < 0. :  #use complementary atan solution; boundary is west of tract centroid\n",
    "                EXITANGLE = pi + EXITANGLE\n",
    "    return EXITANGLE # this reorients 0th wedge to face boundary's closest point\n",
    "\n",
    "def getNewAngles(mWP, tWP, ADP, LEVEL_L, MINADJRATIO, MAXANGLE, MAXANGLERATIO, nUNFILLEDWEDGES): \n",
    "    \"\"\"\n",
    "    This method classifies Home Districts based on how their post-reoriented equi-angle max wedge pops stack up vs targets,\n",
    "     then changes wedge angles in some situations to pick up more population along the boundary\n",
    "    If there is one wedge that will fall short of a quarter district pop, then we adjust angles if it is sufficiently short    \n",
    "    (Using \"HD2\" code, the opposite wedge's pop will be constrained as well.)\n",
    "    If there are two opposite-facing constrained wedges, we do not adjust angles\n",
    "    If there are two adjacent constrained wedges, we classify as a corner (no angle change) if the adjacent wedge is sufficiently constrained,\n",
    "      otherwise we treat as a single constrained wedge\n",
    "    If there are three constrained wedges, the angles are unchanged; we use the 4th wedge to pick up all pop\n",
    "    If all four wedges are constrained, there is an error and we raise a flag.\n",
    "    mWP is the quadlist of maxWedgePops we would get by extending each wedge to the MAP boundary\n",
    "    tWP is the quadlist of targetWedgePops\n",
    "    LEVEL_L is the non-dimensional distance to the boundary at which we no longer adjust wedge angles to drive more near-boundary pop\n",
    "    MAXANGLERATIO is the max ratio of the wide angle (facing the boundary) to the normal angle (e.g. 90deg for four wedges) ...\n",
    "    but this is truncated near-boundary to MAXANGLE (e.g. 1.8 pi/2 instead of increasing all the way to 1.9 pi/2)\n",
    "      NOTE THAT this code does not consider nearly-shorted wedges -- those are a separate method called later if all mWP's > tWP's\n",
    "    \"\"\"   \n",
    "    isChange = False   #default; we are NOT changing angles\n",
    "    printDebuggg = False\n",
    "    NWEDGES = len(mWP)\n",
    "    avgWedgeAngle = 2.*math.pi / NWEDGES\n",
    "    minW = mWP.index(np.min(mWP))  #index of the wedge with the lowest max wedge pop\n",
    "    oppW = int( int(minW + NWEDGES/2) % NWEDGES )  #and its opposing wedge\n",
    "    Lstar = ( mWP[minW] / (0.25*ADP) )**0.5  #shortest wedge's nondim'l distance to boundary\n",
    "    \n",
    "    case = \"keep same wedge angles\" #default; no unfillable wedges or all but one are unfillable\n",
    "    if nUNFILLEDWEDGES >= NWEDGES:\n",
    "        raise Exception(\"ERROR! ALL WEDGES ARE CONSTRAINED for tract\",t,\".  IMPOSSIBLE!!\")\n",
    "    if nUNFILLEDWEDGES == 1:\n",
    "        case = \"constrain opp wedge\"\n",
    "        if Lstar >= levelL :\n",
    "            case = \"keep same wedge angles\"  #not close enough to boundary to distort HD shape\n",
    "    if nUNFILLEDWEDGES == 0 or nUNFILLEDWEDGES == NWEDGES - 1:  #far from boundary or with only one wedge w/large pop\n",
    "        case = \"keep same wedge angles\"   \n",
    "    if nUNFILLEDWEDGES == 2:  #must determine if opposite or adjacent           \n",
    "        if mWP[oppW] < tWP[oppW]:  #shorted wedges oppose each other, so ...\n",
    "            case = \"keep same wedge angles\" #...the HD shape will naturally widen to pick up adjacent pop\n",
    "        else:  #we have 2 adjacent (non-opposing) shorted wedges... but how shorted?  ID the adjacent wedge\n",
    "            for nW in range(NWEDGES):\n",
    "                if mWP[nW] < tWP[nW] and nW != minW :\n",
    "                    adjW = nW  #this is the adjacent wedge\n",
    "                    adjRatio = mWP[adjW] / tWP[adjW]\n",
    "            if adjRatio < minAdjRatio:  #we're close to a corner (this adjacentWedge is significantly constrained)\n",
    "                case = \"keep same wedge angles\"\n",
    "                if printDebuggg :\n",
    "                    print(\"Not adjusting wedge angles for tract\",t,\"as 2nd-sparsest wedge\",adjW,\"has pop\",mWP[adjW] )\n",
    "            else:\n",
    "                case = \"constrain opp wedge\"  #we will set the angles and target pops as if the adj wedge were not constrained\n",
    "    \n",
    "    if case == \"keep same wedge angles\":\n",
    "        isChange = False\n",
    "        WEDGEANGLE = [avgWedgeAngle for w in range(NWEDGES) ]\n",
    "\n",
    "    if case == \"constrain opp wedge\":  #Here, we modify wedge angles.  MWP's will be recalc'd outside the method\n",
    "        isChange = True  \n",
    "        wideAngle = min(MAXANGLE, avgWedgeAngle*max(  1,( 1.+(MAXANGLERATIO-1.)*(LEVEL_L - Lstar)/(LEVEL_L - 0.) )  ) )\n",
    "        WEDGEANGLE = [(2.*pi - 2. * wideAngle)/ (NWEDGES - 2.) for w in range(NWEDGES) ]  \n",
    "        WEDGEANGLE[minW] = wideAngle\n",
    "        WEDGEANGLE[oppW] = wideAngle\n",
    "    \n",
    "    return isChange, WEDGEANGLE\n",
    "\n",
    "def rebalanceTWPs(MWP, TWP, BARREDLIST=list()):\n",
    "    \"\"\"\n",
    "    This method iteratively increases targetWedgePops to accommodate wedges that have maxWedgePop < targetWedgePop.\n",
    "    The wedgePop gap is distributed equally among wedges that have some capacity and are not BARRED (e.g. an opposite wedge in HD2 method)\n",
    "     (If this pushes some wedges over capacity, this will be fixed in a later run through loop inside this method)\n",
    "    We also flag which wedges \"will fill\" = have sufficient capacity after the rebalancing of the targets to not use the entire maxWedgePoly\n",
    "    \"\"\"\n",
    "    DEBUGrTWP = False\n",
    "    NWEDGES = len(MWP)\n",
    "    unorderedCapacity = [MWP[w] - TWP[w] for w in range(NWEDGES) ]\n",
    "    idx = np.argsort(unorderedCapacity)\n",
    "    #for nn in range(NWEDGES):\n",
    "    #    print(MWP[idx[nn]])\n",
    "    if np.min(TWP) < 0.99 * np.average(TWP) and DEBUGrTWP:  #debug\n",
    "        for nn in range(NWEDGES):\n",
    "            print(\"barred list, orig MWP, TWP\",BARREDLIST, r3(MWP[nn]),r3(TWP[nn]) )\n",
    "    \n",
    "    for nn in range(NWEDGES):  #going from least to most maxWedgePop here ...\n",
    "        nW = idx[nn]\n",
    "        if MWP[nW] < TWP[nW]: #need to redistribute extra target to higher-capacity wedges ...\n",
    "            wedgePopGap = TWP[nW] - MWP[nW]\n",
    "            TWP[nW] = MWP[nW]  #max out this wedge\n",
    "            nReceivers = 0.\n",
    "            for WW in range(NWEDGES):\n",
    "                if MWP[WW] > TWP[WW] and WW not in BARREDLIST:  #this wedge could take at least a little more ....\n",
    "                    nReceivers += 1.\n",
    "            for WW in range(NWEDGES):\n",
    "                if MWP[WW] > TWP[WW] and WW not in BARREDLIST:  #this wedge could take at least a little more ....                    \n",
    "                    TWP[WW] += wedgePopGap / nReceivers  #... so give it equal share of the gap, even if this goes over; we'll correct in later loop\n",
    "                    \n",
    "    WILLFILL = [1]*NWEDGES\n",
    "    for nW in range(NWEDGES):\n",
    "        if MWP[nW] < 1.001* TWP[nW]:  #required pop nearly or truly requires the entire wedge\n",
    "            WILLFILL[nW] = 0 \n",
    "    if np.min(TWP) < 0.99 * np.average(TWP) and DEBUGrTWP:  #debug\n",
    "        print(\"adjusted TWP's are\",TWP)\n",
    "    return TWP, WILLFILL\n",
    "\n",
    "def solveWedge(nontractTWP,t, hC, STARTANGLE, ENDANGLE, MAXD, TOLERPOPS, tractCP, tractPop,\n",
    "               countyTractList, countyGeom, countyPop, neighborCountyLIST,XSCALE=1.0):\n",
    "    \"\"\"\n",
    "    #### NO LONGER USED; SEE FASTER SOLVEWEDGEB BASED ON UNIT-UNIT DISTANCES  *********\n",
    "    This heart of the code solves the wedge radius that gives the closest wedgePop to the TargetWedgePop (which excludes the home tractPop)\n",
    "    The wedge has a fixed starting and ending angle.  Its maximum diameter is angle-related to max diameter of the state map\n",
    "    It uses bisection, NOT scipy minimize to minimize the square error in the wedge pop vs. target\n",
    "    The method passes back the final wedge pop and list of tracts in the wedge\n",
    "    \"\"\"\n",
    "    chgLoopNo, maxLoopNo = 10., 22.  #when we will start relaxing the pop tolerance, and when we give up\n",
    "    includedAngl = ENDANGLE - STARTANGLE\n",
    "    guessedR = MAXD / math.cos(0.5*includedAngl)  #max possible wedge radius, accounting for possible wide angle\n",
    "    popTol = TOLERPOPS[0]  #default tolerance = e.g. within 0.7 an AVERAGE tract's population.\n",
    "    #                      We loosen toward half the MAX tractPop if not converging\n",
    "    \n",
    "    offsetPop = 88888888.  #to force a reduction the first time through the loop\n",
    "    dr = guessedR\n",
    "    loopNo = 0\n",
    "    while abs(offsetPop) > popTol and loopNo < maxLoopNo:\n",
    "        loopNo +=1\n",
    "        popTol = max(TOLERPOPS[0], TOLERPOPS[0] + (TOLERPOPS[1] - TOLERPOPS[0]) * (loopNo - chgLoopNo) / (maxLoopNo - chgLoopNo) )\n",
    "        dr = 0.5*dr\n",
    "        guessedR -= dr*np.sign(offsetPop)\n",
    "        \n",
    "        guessedPoly = buildWedge(tractCP[t],STARTANGLE, ENDANGLE, guessedR,XSCALE) \n",
    "        iCP, iClist =  getCountyWP(t,guessedPoly, tractCP, tractPop, countyTractList[hC])\n",
    "        nonCP, nonClist = getNonCWP(guessedPoly, hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyLIST)\n",
    "        offsetPop = iCP + nonCP - nontractTWP\n",
    "        #print(t,loopNo,r5(guessedR),int(iCP),int(nonCP),r3(offsetPop+nontractTWP),r3(nontractTWP),\"t,loop,R,iCP,nonCP,pop,target\")\n",
    "        if loopNo >= maxLoopNo-1:\n",
    "            print(\"WARNING. Looped\",loopNo,\"times for t,angles,R\",t,r3(STARTANGLE),r3(ENDANGLE),r5(guessedR),\n",
    "                  \"wedgePop offset, target are\",int(offsetPop), int(nontractTWP) )    \n",
    "    finalPop = iCP + nonCP\n",
    "    finalList = iClist + nonClist\n",
    "    return finalPop, finalList, guessedR, loopNo\n",
    "\n",
    "#above = bisection.  Below solveWedgeB uses static unit-unit distances\n",
    "# Also tried scipy minimize, which doesn't seem any faster\n",
    "\n",
    "def solveWedgeB(nontractTWP,T, HC, POLLY, TOLERPOP, TRACTCP, TRACTPOP, COUNTYNO,\n",
    "               COUNTYTRACTLIST, COUNTYGEOM, NEIGHBORCOUNTYLIST, UUDIST):\n",
    "    \"\"\"\n",
    "    This heart of the code solves the wedge radius that gives the closest wedgePop to the TargetWedgePop\n",
    "    We first determine which counties intersect the maxWedgePop to reduce the candidate list\n",
    "    We then go through the tract list from closest to farthest, adding any (from candidate counties) that intersect,\n",
    "     until the target pop is reached. Note that the passed UUDIST is the slice for unit t, not the full 2x2 array\n",
    "    \"\"\"\n",
    "    popTol = TOLERPOP  #default tolerance = e.g. within 0.7 an AVERAGE tract's population.\n",
    "    \n",
    "    #preliminary - restrict the found units to those in contiguous counties to the home county\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "        latestClist = newClist.copy()\n",
    "    \n",
    "    idx = np.argsort(UUDIST)  #sort order from closest to farthest to the home unit\n",
    "    \n",
    "    i, capturedPop, capturedList = 0, 0, list()\n",
    "    notFull = True\n",
    "    while notFull :  #capturedPop < nontractTWP - popTol : \n",
    "        i +=1    #this skips over the home tract\n",
    "        TT = idx[i]\n",
    "        if COUNTYNO[TT] in intersectedClist and TT != T:  #just to be sure\n",
    "            if POLLY.contains(TRACTCP[TT]):\n",
    "                capturedPop += TRACTPOP[TT]\n",
    "                capturedList.append(TT)\n",
    "                latestDist = UUDIST[TT]\n",
    "            if capturedPop > nontractTWP - popTol:\n",
    "                notFull = False\n",
    "                \n",
    "    return capturedPop, capturedList, latestDist    \n",
    "\n",
    "def solveWedgeC(nontractTWP,T, HC, POLLY, STARTANGL, ENDANGL, TOLERPOP, TRACTCP, TRACTPOP, COUNTYNO,\n",
    "               COUNTYTRACTLIST, COUNTYGEOM, NEIGHBORCOUNTYLIST, UUDIST, UUANGLE):\n",
    "    \"\"\"\n",
    "    This heart of the code solves the wedge radius that gives the closest wedgePop to the TargetWedgePop\n",
    "    We first determine which counties intersect the maxWedgePop to reduce the candidate list\n",
    "    We then go through the tract list from closest to farthest, adding any (from candidate counties) that\n",
    "    fall within the angle range (in lieu of wedgeB's check for intersection),\n",
    "     until the target pop is reached. Note that the passed UUDIST is the slice for unit t, not the full 2D array\n",
    "    \"\"\"\n",
    "    pi = 3.141592653\n",
    "    popTol = TOLERPOP  #default tolerance = e.g. within 0.7 an AVERAGE tract's population.\n",
    "    STARTANGL, ENDANGL = STARTANGL % (2.*pi), ENDANGL % (2.*pi)\n",
    "    #preliminary - restrict the found units to those in contiguous counties to the home county\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "        latestClist = newClist.copy()\n",
    "    \n",
    "    idx = np.argsort(UUDIST)  #sort order from closest to farthest to the home unit\n",
    "    \n",
    "    i, capturedPop, capturedList, latestDist = 0, 0, list(), 0.00001  #dummy value\n",
    "    notFull = True\n",
    "    while notFull and i < len(UUDIST) - 2 :  #capturedPop < nontractTWP - popTol : \n",
    "        i +=1    #this skips over the home tract\n",
    "        TT = idx[i]\n",
    "        if COUNTYNO[TT] in intersectedClist and TT != T:  #just to be sure\n",
    "            if isIncludedA(STARTANGL, ENDANGL, UUANGLE[TT]) : #POLLY.contains(TRACTCP[TT]):\n",
    "                capturedPop += TRACTPOP[TT]\n",
    "                capturedList.append(TT)\n",
    "                latestDist = UUDIST[TT]\n",
    "            if capturedPop > nontractTWP - popTol:\n",
    "                notFull = False\n",
    "                \n",
    "    return capturedPop, capturedList, latestDist \n",
    "\n",
    "\n",
    "def getPartialTract(t, HDTRACTLIST, offsetPop, UUDIST, tractPop, neighborLIST):\n",
    "    \"\"\"\n",
    "    If offsetPop is >0, this method identifies the tract with centroid farthest from Home t that can jettison at least offsetPop ...\n",
    "    ... by slicing out part of this tract.\n",
    "    If offsetPop <0, we ID a tract CLOSEST to Home t among neighbors of in-HD tracts to pick up a partial\n",
    "    We return the tractID and its new partial use\n",
    "    We have updated this method to pass the uuDist slice for tract t instead of computing tract distances inside here\n",
    "    \"\"\"\n",
    "    debugGPT = False\n",
    "    NTRACTS = len(tractCP)\n",
    "    bigDist = 9999999.\n",
    "    qualifyingTractList = list()\n",
    "    isWholeTract = False\n",
    "    if offsetPop > 0:\n",
    "        homeDist = [0.]*NTRACTS  #default = 0 to not get picked\n",
    "        for TT in HDTRACTLIST:\n",
    "            if tractPop[TT] > offsetPop:\n",
    "                qualifyingTractList.append(TT)\n",
    "        for TT in qualifyingTractList:\n",
    "            homeDist[TT] = UUDIST[TT]\n",
    "        if len(qualifyingTractList) == 0:  #very rare case where all in-HD tracts are too small.  Jettison nearly the whole farthest one\n",
    "            isWholeTract = True\n",
    "            for TT in HDTRACTLIST:\n",
    "                if tractPop[TT] > 0.9*np.average(tractPop): #set arbitrary min qualifying pop\n",
    "                    homeDist[TT] = UUDIST[TT]\n",
    "        targetT = homeDist.index(np.max(homeDist))\n",
    "        partialUseFrac = max(0.0001,(tractPop[targetT] - offsetPop)/tractPop[targetT] )\n",
    "        if debugGPT:\n",
    "            print(\"positive offsetPop =\",offsetPop,\", ID'd tract\",targetT,\"with pop\",tractPop[targetT] )\n",
    "    else: #pick up a partial\n",
    "        homeDist = [bigDist]*NTRACTS\n",
    "        for TT in HDTRACTLIST:\n",
    "            for TTT in neighborList[TT]:\n",
    "                if TTT not in qualifyingTractList and TTT not in HDTRACTLIST and tractPop[TTT] > abs(offsetPop):\n",
    "                    qualifyingTractList.append(TTT)\n",
    "        for TTT in qualifyingTractList:\n",
    "            homeDist[TTT] = UUDIST[TTT]\n",
    "        if len(qualifyingTractList) == 0 :  #rare case where most nearby tracts are small.  Add nearly the whole biggest one\n",
    "            isWholeTract = True\n",
    "            maxPop = 0.\n",
    "            targetT = -999\n",
    "            for TT in HDTRACTLIST:\n",
    "                for TTT in neighborList[TT]:\n",
    "                    if TTT not in qualifyingTractList and TTT not in HDTRACTLIST : # we'll take just one, even if doesn't fill gap\n",
    "                        qualifyingTractList.append(TTT)\n",
    "            for TTT in qualifyingTractList:\n",
    "                if tractPop[TTT] > maxPop:\n",
    "                    targetT = TTT\n",
    "                    maxPop = tractPop[targetT]\n",
    "        else:\n",
    "            targetT = homeDist.index(np.min(homeDist))\n",
    "        partialUseFrac = min(0.9999, -1.* offsetPop/tractPop[targetT] )\n",
    "        if debugGPT:\n",
    "            print(t,\"'s negative offsetPop =\",offsetPop,\", ID'd tract\",targetT,\"with pop\",tractPop[targetT] )\n",
    "    \n",
    "    return targetT, partialUseFrac\n",
    "\n",
    "def getAdjoiners(UNITLIST, UNITNBRS): #returns all units that neighbor a UNITLIST but are not in the UNITLIST \n",
    "    allNbrs = list()\n",
    "    for U in UNITLIST:\n",
    "        allNbrs = allNbrs + UNITNBRS[U]\n",
    "    adjoiners = list( set(allNbrs).difference(set(UNITLIST)) )\n",
    "    return adjoiners\n",
    "\n",
    "def get2nbrs(ULIST, UNITNBRS):\n",
    "    \"\"\"\n",
    "    Get the combined list of first- and second-level neighbors of a LIST, using neighborList connectivity.  Excludes the source list\n",
    "    \"\"\"\n",
    "    firstList =  getAdjoiners(ULIST, UNITNBRS)\n",
    "    secondList = getAdjoiners(firstList, UNITNBRS)\n",
    "    twoLevelList = list( set(firstList + secondList).difference(set(ULIST) ) )\n",
    "    return twoLevelList\n",
    "\n",
    "def getContigFromStarter(starter, VLIST, NEIGHBORLIST):  #all contiguous units in VLIST, starting from starter unit\n",
    "    foundList, newList, prevList = [ starter ], [ starter ], [ starter ]\n",
    "    while len(newList) > 0:\n",
    "        newList = list()\n",
    "        for V in prevList:\n",
    "            for VV in NEIGHBORLIST[V]:\n",
    "                if VV in VLIST and VV not in foundList:\n",
    "                    newList.append(VV)\n",
    "                    foundList.append(VV)\n",
    "        prevList = newList.copy()        \n",
    "    return foundList   \n",
    "\n",
    "def isContiguous(VLIST,NEIGHBORLIST,returnBiggestPiece=False):\n",
    "    \"\"\"\n",
    "    This method determines if all items in a list form a continuous chain of neighbors based on the passed neighborlist\n",
    "    Empty lists are considered contiguous.  If discontiguous, a less-than-majority piece list is returned,\n",
    "     unless giveBig=True, in which case we return the biggest piece\n",
    "    \"\"\"    \n",
    "    isUnbroken, newList, foundList = True, list(), list()\n",
    "    if len(VLIST) > 0:\n",
    "        foundList, newList, prevList = [ VLIST[0] ], [ VLIST[0] ], [ VLIST[0] ]\n",
    "    while len(newList) > 0:  #this round's list of neighbors\n",
    "        newList = list()\n",
    "        for V in prevList:\n",
    "            for VV in NEIGHBORLIST[V]:\n",
    "                if VV in VLIST and VV not in foundList:\n",
    "                    newList.append(VV)\n",
    "                    foundList.append(VV)\n",
    "        prevList = newList.copy()      \n",
    "    pickedPieceList = foundList.copy()  #default contiguous sublist to pass back to main\n",
    "    \n",
    "    if len(foundList) < len(VLIST):  #not contiguous\n",
    "        isUnbroken  = False\n",
    "        pieceLists, remainingList = [foundList], list( set(VLIST).difference(set(foundList) ) )\n",
    "        if returnBiggestPiece == True:  #we were asked for the biggest piece, not a random small one, so we must find them all\n",
    "            if len(foundList) < 0.5*len(VLIST):\n",
    "                while len(remainingList) > 0:\n",
    "                    newList = getContigFromStarter(remainingList[0], remainingList, NEIGHBORLIST)\n",
    "                    pieceLists.append(newList)\n",
    "                    remainingList = list(set(remainingList).difference(set(newList)))\n",
    "                pieceLengths = [len(pL) for pL in pieceLists]\n",
    "                pickedPieceList = pieceLists[ pieceLengths.index(np.max(pieceLengths)) ]\n",
    "            \n",
    "        else: #quickly return a contiguous sub-list that's at most half the total units in the list\n",
    "            if len(foundList) > 0.5*len(VLIST): #pick a different piece; this one is the majority\n",
    "                pickedPieceList = getContigFromStarter(remainingList[0], remainingList, NEIGHBORLIST)\n",
    "                \n",
    "    return isUnbroken, pickedPieceList\n",
    "\n",
    "def enclaveCheck(UNITLIST,UNITNBRS,maxLoops=4):\n",
    "    \"\"\"\n",
    "    This method determines if a list of units has an unbroken boundary AND whether its complement has an unbroken boundary\n",
    "    If the complement boundary is broken, there is an enclave or the district is so disconnected its adjoining units aren't contiguous\n",
    "    The method returns contiguity of boundary and of its adjoiners.  Also returns the lists of boundary and complement-boundary units\n",
    "      If either of these is broken, only a contiguous sublist is returned that is guaranteed to be smaller than half (for finding enclaves)\n",
    "      maxLoops is the number of loops for expanding neighbors-of-neighbors for contiguity of the units outside the passed unit-list\n",
    "    \"\"\"\n",
    "    UNITSET = set(UNITLIST)\n",
    "    ADJLIST =  get2nbrs(UNITLIST, UNITNBRS)  #in case direct adjoiners are only queen-adjacent\n",
    "    #adjoinersOfAdjoiners = getAdjoiners(ADJLIST,  UNITNBRS)\n",
    "    #BDRYLIST = list( set(UNITLIST).intersection(set(adjoinersOfAdjoiners)) )  #this might fail for queen-adjacent boundary units\n",
    "    BDRYLIST = list (set(get2nbrs(ADJLIST,UNITNBRS)).intersection(UNITSET) )  #in case inHD boundary is only queen-adjacent\n",
    "    noEnclave, enclaveList =   isContiguous(ADJLIST, UNITNBRS)  \n",
    "    unbroken, smallPieceList = isContiguous(BDRYLIST, UNITNBRS)\n",
    "    if not unbroken: #could be that district's boundary intersects the state boundary or there is a nonHD enclave inside the HD\n",
    "        unbroken, smallPieceList = isContiguous(UNITLIST, UNITNBRS)  #slower check for full district, not just its boundary \n",
    "    nLoops = 1 #could be that fragmented adjoining districts are underestimating true contiguity.  Widen the contig search\n",
    "    while nLoops <= maxLoops and not noEnclave:\n",
    "        nLoops +=1\n",
    "        newSet = set(ADJLIST)\n",
    "        for UU in ADJLIST:\n",
    "            newSet = newSet.union( set(UNITNBRS[UU]).difference(UNITSET) )\n",
    "        ADJLIST = list(newSet)\n",
    "        noEnclave, enclaveList =   isContiguous(ADJLIST, UNITNBRS)\n",
    "    #isJiggy = noEnclave and unbroken\n",
    "    return unbroken, noEnclave, smallPieceList, enclaveList\n",
    "\n",
    "def getBdryNonEdgers(UNITLIST, UNITNBRS): #all in-district boundary units that neighbor a non-district unit\n",
    "    ALLnonHDnbrs = set()\n",
    "    for UUU in UNITLIST:\n",
    "        ALLnonHDnbrs = ALLnonHDnbrs.union(set(UNITNBRS[UUU])).difference(set(UNITLIST))\n",
    "    BdryNonEdgerSet = set()\n",
    "    for UUU in UNITLIST:\n",
    "        if len(set(UNITNBRS[UUU]).intersection(ALLnonHDnbrs)) > 0:\n",
    "            BdryNonEdgerSet.add(UUU)\n",
    "    return list(BdryNonEdgerSet)\n",
    "\n",
    "def getEnclaveLists(UNITLIST, UNITNBRS):\n",
    "    \"\"\"\n",
    "    finds ALL units enclaved by a UNITLIST, parsed into lists of contiguous pieces\n",
    "    We assume the largest contiguous complement to the UNITLIST is not an enclave, but rather the majority of the HD complement\n",
    "    if the UNITLIST's complement (all couldBeEnclaved) is contiguous, the returned list will be blank\n",
    "    \"\"\"\n",
    "    eSets, nU = list(), len(UNITNBRS)\n",
    "    offmapList = list()\n",
    "    for i,L in enumerate(UNITNBRS):\n",
    "        if len(L) == 0:\n",
    "            offmapList.append(i)  #offmap list are units with no neighbors (were surrounded)\n",
    "    complementSet = set([i for i in range(nU)] ).difference( set(UNITLIST + offmapList) )    \n",
    "    remaining2nbrs = get2nbrs(UNITLIST, UNITNBRS)\n",
    "    \n",
    "    isContig, shortList = isContiguous(remaining2nbrs,UNITNBRS) #quicker than contig check on entire complement\n",
    "    while not isContig:  #this will kick out before writing the final sublist = map majority\n",
    "        starter = shortList[0]\n",
    "        newEnclaveList = getContigFromStarter(starter, list(complementSet), UNITNBRS)\n",
    "        eSets.append(set(newEnclaveList))\n",
    "        remaining2nbrs = list(set(remaining2nbrs).difference(set(shortList)) )\n",
    "        isContig, shortList = isContiguous(remaining2nbrs,UNITNBRS)\n",
    "        \n",
    "        # couldBeEnclaved = list( set(couldBeEnclaved).difference(set(newEnclaveList)) )  #revised 18-Feb-24 -- was slower\n",
    "    fused_eSets = set()\n",
    "    for i, eSet in enumerate(eSets):\n",
    "        fused_eSets = fused_eSets.union(eSet)\n",
    "        for j in range(i+1, len(eSets) ) :\n",
    "            eSets[j] = eSets[j].difference(eSet)  #in case contiguity occurs, but not in 2-neighbor list; avoid double-count\n",
    "    remnant_eSet = complementSet.difference(fused_eSets) \n",
    "    eLengths = [len(eSet) for eSet in eSets]\n",
    "    if len(eSets) > 0:\n",
    "        if len(remnant_eSet) < np.max(eLengths):  #exchange the small remnant for the biggest found \"enclave\" (usually the major complement) \n",
    "            eSets[eLengths.index(np.max(eLengths))] = remnant_eSet.copy()\n",
    "    eLists = [list(eSet) for eSet in eSets]\n",
    "    return eLists\n",
    "\n",
    "def wontEnclave(proposedU, dList, NBRLIST, mapBDRYLIST):\n",
    "    \"\"\"\n",
    "    This method checks if adding a proposedU to a dList (list of units in a district) will create an \"enclave\" of units in the dList's complement\n",
    "    via two problems:  A) the dList will now have a discontiguous set of units on the map boundary.  The full map boundary list is mapBDRYLIST\n",
    "      B) The non-dList neighbors of dList units aren't contiguous\n",
    "    The method doesn't require that the dList wontEnclave without the proposedU included; it just checks the proposedU + dList combination\n",
    "    It also doesn't check that the dList is itself contiguous with or without proposedU\n",
    "    In that sense, it is more limited than enclaveCheck\n",
    "    \"\"\"\n",
    "    wontEnclave = True\n",
    "    newList, newSet = dList + [proposedU], set(dList + [proposedU])\n",
    "    unitsOnBoundary = list( set(mapBDRYLIST).intersection(newSet) )\n",
    "    wontEnclave, __ = isContiguous(unitsOnBoundary,NBRLIST)  #first check - does district touch MAP boundary in multiple places? (quick FAIL)\n",
    "    if wontEnclave: #slower check below for internal enclaves\n",
    "        adjoiners = get2nbrs(newList, NBRLIST)  #2-level to protect for queen adjacency in boundary        \n",
    "        wontEnclave, __ = isContiguous(adjoiners,NBRLIST)\n",
    "        if not wontEnclave:\n",
    "            nLoops = 1 #could be that fragmented adjoining districts are underestimating true contiguity.  Widen the contig search\n",
    "            maxLoops, ADJLIST = 6, adjoiners #unlike enclaveCheck, here we just arbitrarily set a number of loops for search expansion\n",
    "            while nLoops <= maxLoops and not wontEnclave:\n",
    "                nLoops +=1\n",
    "                adjSet = set(ADJLIST)  #align nomenclature w enclaveCheck\n",
    "                for UU in ADJLIST:\n",
    "                    adjSet = adjSet.union( set(NBRLIST[UU]).difference(set(newList)) )\n",
    "                ADJLIST = list(adjSet)\n",
    "                wontEnclave, __ =   isContiguous(ADJLIST, NBRLIST)\n",
    "        \n",
    "    return wontEnclave"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d041d328-83e0-45db-a869-e0956c23ee26",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter the state postal code; e.g. OH  NJ\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK, enter 1 below to use nj_pl2020_vtd.dbf as this state's population data file\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "  1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "attempting to read in state unit geometries.  Stand by ...\n",
      "I read in the Census popn data. NJ has 9288994 peeps and is divided into 6361 shapes.\n"
     ]
    }
   ],
   "source": [
    "STATE = str(input(\"Enter the state postal code; e.g. OH \")).upper()\n",
    "popFilename = STATE.lower()+\"_pl2020_vtd.dbf\"\n",
    "print(\"OK, enter 1 below to use\",popFilename,\"as this state's population data file\")\n",
    "enter1 = input(\" \")\n",
    "if int(enter1) != 1:\n",
    "    popFilename = input(\"OK, then enter the pop data file.  Typically a xx_pl2020_vtd.dbf\")\n",
    "print(\"attempting to read in state unit geometries.  Stand by ...\")\n",
    "tractPopFile = gpd.read_file(\"state_map_files/\"+popFilename)\n",
    "trueTractGeom = tractPopFile['geometry']\n",
    "nTracts = len(trueTractGeom)\n",
    "tractPop = tractPopFile['P0010001']\n",
    "statePop = np.sum(tractPop)\n",
    "censusGEOID20 = tractPopFile['GEOID20']\n",
    "print(\"I read in the Census popn data.\",STATE,\"has\",statePop,\"peeps and is divided into\",nTracts,\"shapes.\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3bfdea9d-b0ea-497a-a556-6b488a3e333e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter the number of districts in the state.  My guess is 12 12\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There appear to be 21 counties in NJ .  I will assign them county Nos 0 - 20\n"
     ]
    }
   ],
   "source": [
    "tractGeom = trueTractGeom.copy()   #for some states, we will modify geom, so preserve original\n",
    "#tractNAME20 = tractPopFile['NAME20']\n",
    "tractPop = tractPopFile['P0010001']\n",
    "inputfileCountyNo = tractPopFile['COUNTYFP20']\n",
    "vtdGEOID20 =  tractPopFile['GEOID20'] \n",
    "nDistricts = int(round(statePop/760000,0))\n",
    "nCutDistricts = 0\n",
    "nDistricts = int(input(\"Enter the number of districts in the state.  My guess is \"+str(nDistricts)))\n",
    "tractArea = [tractGeom[t].area for t in range(nTracts)]\n",
    "trueTractCP =   [tractGeom[t].centroid for t in range(nTracts)]\n",
    "tractCP = trueTractCP.copy()  #for some states, we move secluded corners into the map, so save the true data\n",
    "tractCPx =  [tractCP[t].x for t in range(nTracts)]\n",
    "tractCPy =  [tractCP[t].y for t in range(nTracts)]\n",
    "inputCountyNumbers = list()\n",
    "for t in range(nTracts):\n",
    "    if inputfileCountyNo[t] not in inputCountyNumbers:\n",
    "        inputCountyNumbers.append(inputfileCountyNo[t])\n",
    "nCounties = len(inputCountyNumbers)\n",
    "print(\"There appear to be\",nCounties,\"counties in\",STATE,\".  I will assign them county Nos 0 -\",int(nCounties-1))\n",
    "sortedICNs = list(np.sort(inputCountyNumbers))\n",
    "countyNo = [sortedICNs.index(inputfileCountyNo[t]) for t in range(nTracts) ]\n",
    "\n",
    "isSkippedTract = [0] *nTracts  #this will house a temporary list of tracts for manipulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "adffc7a4-a78c-477f-8ea4-7f8e5109fa2a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We will now build the county-by-county geometries, hoping there are no islands\n",
      "Building county geom for county 0\n",
      "Building county geom for county 20\n",
      "Here is your original county-based map b4 any triage; e.g eliminating coastal unpopulated tracts w pop < 4.5\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There appear to be 5 unpopulated coastal tracts.  Lets plot them and their parent counties\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"We will now build the county-by-county geometries, hoping there are no islands\")\n",
    "skipList = list()  #a list of units we previously know to skip in the map\n",
    "isAlteredCounty = [False for c in range(nCounties)]\n",
    "countyTractList = [list() for c in range(nCounties)]\n",
    "countyPop =       [0. for c in range(nCounties)]\n",
    "countyGeom =      [dummyPoly for c in range(nCounties)]\n",
    "for t in range(nTracts):\n",
    "    if t not in skipList:\n",
    "        c = countyNo[t]\n",
    "        countyTractList[c].append(t)\n",
    "        countyPop[c] += tractPop[t]\n",
    "for c in range(nCounties):\n",
    "    if c%20 == 0:\n",
    "        print(\"Building county geom for county\",c)\n",
    "    for t in countyTractList[c]:\n",
    "        if countyGeom[c] == dummyPoly:\n",
    "            countyGeom[c] = tractGeom[t]\n",
    "        else:\n",
    "            countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "origMAP = countyGeom[0]\n",
    "for c in range(nCounties):\n",
    "    origMAP = origMAP.union(countyGeom[c])\n",
    "    if countyGeom[c] == dummyPoly:\n",
    "        print(\"WARNING! county\",c,\"is empty!\")\n",
    "    else:\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c,countyGeom[c])\n",
    "minTractPop = 4.5\n",
    "print(\"Here is your original county-based map b4 any triage; e.g eliminating coastal unpopulated tracts w pop <\",minTractPop)\n",
    "plt.show()\n",
    "if origMAP.geom_type == dummyPoly.geom_type:\n",
    "    mapExterior = origMAP.exterior\n",
    "else:\n",
    "    for i,geo in enumerate(origMAP.geoms):\n",
    "        if i == 0:\n",
    "            mapExterior = geo.exterior\n",
    "        else:\n",
    "            mapExterior = mapExterior.union(geo.exterior)\n",
    "\n",
    "for c in range(nCounties):\n",
    "    for t in countyTractList[c]:\n",
    "        if tractPop[t] < minTractPop:\n",
    "            if tractGeom[t].intersects(mapExterior):\n",
    "                isAlteredCounty[c] = True\n",
    "                skipList.append(t)\n",
    "print(\"There appear to be\",len(skipList),\"unpopulated coastal tracts.  Lets plot them and their parent counties\")\n",
    "for t in skipList:\n",
    "    plotPoly(tractGeom[t])\n",
    "    plotCenter(t,tractGeom[t],6)\n",
    "plotPoly(origMAP,0.2)\n",
    "for c in range(nCounties):\n",
    "    if isAlteredCounty[c]:\n",
    "        plotPoly(countyGeom[c])\n",
    "plt.show()\n",
    "trueMAP = origMAP  #use these terms interchangeably"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "7a6c93c4-af08-47d5-90f7-dc0b4513aad5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Last chance to alter the skipList, otherwise the above 5 units will be axed\n",
      "here is the proposed skipList [6267, 1831, 1293, 5386, 2086]\n",
      "here is the final skipList [6267, 1831, 1293, 5386, 2086]\n"
     ]
    }
   ],
   "source": [
    "print(\"Last chance to alter the skipList, otherwise the above\",len(skipList),\"units will be axed\")\n",
    "print(\"here is the proposed skipList\", skipList)\n",
    "#skipList = [1939, 1364] #...  #alter here if needed - 1874, 1270, 1497, 1771 create contiguity problems if axed\n",
    "print(\"here is the final skipList\", skipList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2989f381-466b-4882-bf1d-cfa37a7ba8ef",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I will now preserve the original county unit lists and geoms, then rebuild as needed\n",
      "removing coastal units from countyNo 0\n",
      "removing coastal units from countyNo 4\n",
      "removing coastal units from countyNo 5\n",
      "removing coastal units from countyNo 12\n",
      "removing coastal units from countyNo 14\n",
      "Here is the revised state county map after eliminating coastal tracts\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Excellent!  We have no populated islands.  SKIP the below code block.\n",
      "we will scale longitudinal distance by 0.76469\n"
     ]
    }
   ],
   "source": [
    "print(\"I will now preserve the original county unit lists and geoms, then rebuild as needed\")\n",
    "trueCountyTractList = [list() for c in range(nCounties)]\n",
    "trueCountyGeom = [countyGeom[c] for c in range(nCounties)]\n",
    "for c in range(nCounties):\n",
    "    trueCountyTractList[c] = countyTractList[c].copy()\n",
    "    if isAlteredCounty[c]:\n",
    "        print(\"removing coastal units from countyNo\",c)\n",
    "        countyTractList[c] = list()\n",
    "        countyGeom[c] = dummyPoly\n",
    "        for t in trueCountyTractList[c]:\n",
    "            if t not in skipList:\n",
    "                countyTractList[c].append(t)\n",
    "                if countyGeom[c] == dummyPoly:\n",
    "                    countyGeom[c] = tractGeom[t]\n",
    "                else:\n",
    "                    countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "        if countyGeom[c] == dummyPoly:\n",
    "            print(\"Uh oh! county\",c,\"didn't have any usable tracts\")\n",
    "MAP = countyGeom[0]\n",
    "for c in range(nCounties):\n",
    "    plotPoly(countyGeom[c])\n",
    "    plotCenter(c,countyGeom[c])\n",
    "    MAP = MAP.union(countyGeom[c])\n",
    "origPopMAP = MAP   #origPopMAP is the map after eliminating coastal unpopulated tracts, with original islands\n",
    "print(\"Here is the revised state county map after eliminating coastal tracts\")\n",
    "plt.show()\n",
    "if MAP.geom_type == dummyPoly.geom_type:\n",
    "    print(\"Excellent!  We have no populated islands.  SKIP the below code block.\")\n",
    "else:\n",
    "    print(\"We appear to have some populated islands.  Separate out the main state geom in next block.\")\n",
    "LAT = MAP.centroid.y\n",
    "xScale = (1. - 1.089* abs(LAT/90)**1.9)\n",
    "print(\"we will scale longitudinal distance by\",r5(xScale))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8a562a21-4107-4a3c-a320-90442a473387",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lets first identify which county each island belongs to.  Then we'll move the island to the closest county mainland\n",
      "unit 286 has island pieces.  We will reduce the tract to its main state component\n",
      "unit 292 has island pieces.  We will reduce the tract to its main state component\n",
      "unit 293 has island pieces.  We will reduce the tract to its main state component\n",
      "unit 294 has island pieces.  We will reduce the tract to its main state component\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unit 3112 has island pieces.  We will reduce the tract to its main state component\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unit 1771 has island pieces.  We will reduce the tract to its main state component\n",
      "unit 1772 has island pieces.  We will reduce the tract to its main state component\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAkAAAAGdCAYAAAD60sxaAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/H5lhTAAAACXBIWXMAAA9hAAAPYQGoP6dpAABRgklEQVR4nO3deXxU1d0/8M+9s2VfSAjZAxhIwhp2SJGlUBBRFPHBx1KwuFVFheJjKW1ti7WFaq32VxeQAmIVcStLFVFEFhGQEAiLQCCYjUAWCJnJOpmZe35/hIyMWSckmeV+3i/nhXPvnTvfk5nJfHLuuedKQggBIiIiIhWRXV0AERERUVdjACIiIiLVYQAiIiIi1WEAIiIiItVhACIiIiLVYQAiIiIi1WEAIiIiItVhACIiIiLV0bq6gI6gKAouXryIwMBASJLk6nKIiIioDYQQqKioQHR0NGS5a/tkvCIAXbx4EXFxca4ug4iIiNqhoKAAsbGxXfqcXhGAAgMDAdT/AIOCglxcDREREbWFyWRCXFyc/Xu8K3lFAGo47BUUFMQARERE5GFcMXyFg6CJiIhIdRiAiIiISHUYgIiIiEh1GICIiIhIdRiAiIiISHUYgIiIiEh1GICIiIhIdRiAiIiISHUYgIiIiEh1GICIiIhIdRiAiIiISHUYgIiIiEh1GICIiIhIdbziavBERM66WnsVp6+chlVYAQCjokbBoDG4uCoi6ioMQESkCpcqL+G88TyEEACAEEMIRkSNgE7WwWKz4FDRIZhtZgyNGIoQnxDXFktEnY4BiIi8jhACOcYcXKi8YF8W5R+FtOg0yFLjI/86jQ4/ivkRhBA4WnIU5SXl6BPSB3FBcV1ZNhF1IQYgIvJ4VsWKrKtZKKspAwBIkoSeQT1xc8zNkCSpzfuRJAlDewwFAJy9ehZf5n+JSP9I9Avr1yl1E5HrMAARkccx28w4deUUKusqAQAaSYO+3fqif1j/DnuOvqF90Te0L4qqivBl/pcI1AdiWI9hTfYgEZHnYQAiIrdXUVeBU1dOoc5WBwDQa/ToF9YPgfrATn/uSP9IRPpHwmg2Yk/BHug0OoyKHAWdRtfpz01EnYcBiIjczuWayzhbdhY2YQMABOgDkBqR6tKztIINwZgYPxG11locuHQAilAwInIE/HX+LquJiNqPAYiIXEoIgcLKQuQYc+zLwnzDMDJqJLSy+/2K8tH6YFzsONgUG9KL0+Gj8UFqRKqryyIiJ7nfbxci8mqKUJBdno3iqmL7spjAGIyNGevUgGVX08gajI4aja8Lv3Z1KUTUDgxARNSpLIoFp6+chtFsBFB/plViSCL6hvZ1cWVEpGYMQETUoaot1Th15RRqrDUAAK2sRXK3ZAzqPsjFlRERfY8BiIhuiNFsxLdXvoVVsUKCBB+tD/qH9Yefzs/VpRERNYsBiIicUlRVhOzybPslJYINwRjRYwRPCycij8IARETNEkIgx5SDCxUXIKF+gHKEX0Szl5Sg5n18/CIMUf4IM2gxNIinzhO5GgMQEdn98JISANAz2PlLSlBjQ+JDERVkgCwzOBK5AwYgIhW7/pISAgJaSdvhl5SgejEhvq4ugYiuwwBEpCI/vKSEQWNASlhKl1xSgojInTAAEXmppmZYdodLShARuQMGICIvcqbsDEqrS+33PXGGZSKirsAAROThhBDILM1EeW05UsJSkNwt2dUlERG5PQYgIg8lhMDh4sOoqKtAakQqhkQMcXVJREQegwGIyMMoQsGhokOotlRjWI9hCDYEu7okIiKPwwBE5CFsig2Hig6h1lqLEZEjEKAPcHVJBEBAuLoEImoHBiAiN2dVrPjm0jewKBaMjBzJa2wREXUABiAiN9UQfKyKFSOjRsJXy4n0iIg6CgMQkZuxKBZ8c+kb2BQbRkWNgo/Wx9UlUQsarpFGRJ6FAYjITTD4EBF1HQYgIhcTQuDApQOw2CwMPkREXYQBiMhFhBDIKM6Asc6IYRHDEOIT4uqSiIhUQ76RB69YsQKSJGHRokX2ZUVFRZg7dy4iIyPh7++PoUOH4qOPPmpxP8uXL8eIESMQGBiIiIgI3HnnncjKyrqR0ojclhAC6UXp2FWwC4khiZgUP4nhh4ioi7U7AKWnp2PVqlUYNGiQw/J58+YhKysLW7duxYkTJ3DXXXdh9uzZOHr0aLP72rNnDxYsWICDBw9ix44dsFgsmDJlCqqqqtpbHpHbUYSCQ5cOYVfBLvQN7Ysfx/+YwYeIyEXadQissrISc+bMwerVq/Hcc885rNu/fz9ef/11jBw5EgDwu9/9Di+99BIyMjIwZEjTU/Vv377d4f6bb76JiIgIZGRkYNy4ce0pkchtNMzcXGOpwfDI4QjUB7q6JOpAnAiRyDO1qwdowYIFmD59OiZPntxoXVpaGt577z2UlZVBURRs3LgRtbW1mDBhQpv3bzQaAQDdunVrcr3ZbIbJZHK4Ebkbm2LDgYsHsKdgDwaEDcDE+IkMP0REbsLpHqCNGzfiyJEjSE9Pb3L9+++/j3vuuQdhYWHQarXw8/PDpk2bkJiY2Kb9K4qCRYsW4Uc/+hEGDBjQ5DbLly/HsmXLnC2dqEtYFSsOXTqEOqWOMzcTEbkppwJQQUEBFi5ciB07dsDHp+lTdZ955hmUl5fjiy++QHh4ODZv3ozZs2fjq6++wsCBA1t9jgULFuDkyZPYt29fs9ssXboUixcvtt83mUyIi4tzpilEHc5ms+Hc+XM4WHkQswfOZvAhInJjkhCizQewN2/ejJkzZ0Kj0diX2Ww2SJIEWZaRlZWFxMREnDx5Ev3797dvM3nyZCQmJmLlypUt7v/xxx/Hli1bsHfvXvTq1avNjTCZTAgODobRaERQUFCbH0fUEaxWK3JycqAoCsIjw3Ew5yCmp053dVnURfYV7sPYmLGuLoPII7ny+9upHqBJkybhxIkTDsvmz5+P5ORkLFmyBNXV1QAAWXYcWqTRaKAoSrP7FULgiSeewKZNm7B7926nwg+Rq1itVnz33XcAgF69ekGn06HUWAqdVufiyoiIqDVOBaDAwMBG43L8/f0RFhaGAQMGwGKxIDExEb/4xS/wt7/9DWFhYdi8eTN27NiBjz/+2P6YSZMmYebMmXj88ccB1B/22rBhA7Zs2YLAwEAUFRUBAIKDg+HrywtAknuxWCzIycmBJEno3bs3tNrvP0Z1tjroNAxARETurkNngtbpdNi2bRt+/etf4/bbb0dlZSUSExOxfv163Hrrrfbtzp8/j8uXL9vvv/766wDQ6EyxdevW4ec//3lHlkjUbhaLBd999x1kWW4UfBqYrWboNXoXVEdERM644QC0e/duh/t9+vRpdebn3Nxch/tODEMi6nJ1dXXIycmBLMtITEx0GAP3QxarhT1AREQegNcCI2qG2WxGTk4OtFptq8GnQZ2tDnote4CIiNwdAxDRD9TW1iI3Nxc6nQ59+/ZtNKi/JXXWOvjqOW6NiMjdMQARXdMQfPR6vdPBp0GdrQ5BGk7FQETk7hiASPVqamqQm5sLg8HQ7uDToM5aB4PW0IHVkbvjGEYiz8QARKrVEHx8fHyQlJR0Q8GngcVm4TxAKiNJkqtLIKJ2YAAi1ampqUFeXh58fHyQnJzcoV9g7AEiIvIMDECkGtXV1cjLy4Ovry+SkpI65S93i2LhWWBERB6AAYi83vXBp6N7fH7IYrWwB4iIyAMwAJHX6srg08AmbBwDRETkARiAyOtUVVUhPz+/S4MPERF5FgYg8hoNwcfPz4/Bh7qMBL7PiDwRAxB5PAYfIiJyFgMQeayG4OPv78/gQy4jwIkQiTwRAxB5nMrKShQUFDD4EBFRuzEAkcdg8CF3xDFARJ6JAYjc3pUrV1BaWuoRY3xMtSZXl0BERG3AAERu6/Lly7h8+TK6deuG5ORkV5fTJkE+vBI8EZEnYAAit1NaWoorV64gLCzMY4JPA1m68QuqEhFR52MAIrdRWFiIiooKhIeHe1zwaaAIxdUlEBFRGzAAkcs1BJ+IiAjExMS4uhwiIlIBBiBymYbgExUV5TXBh4fA1IfzABF5JgYg6nKFhYUwmUyIjo72muDTgIfAiIg8AwMQdRlvDj6kXpwHiMgzMQBRp1NT8OEhMCIiz8AARJ1GTcGnAQ+BERF5BgYg6nBqDD6kXhwETeSZGICow3jjWV3O4iEwIiLPwABEN4zB53s8BEZE5BkYgKjdeKiLiGeBEXkqBiByGoNP83gIjIjIMzAAUZsx+LSOh8DUh4OgiTwTAxC1isGHiIi8DQMQNYvBx3k8BEZE5BkYgKgRBp/2sVgtDEAqxEHQRJ6JAYjsGHxujMVmgVbDj5TacAwQkWfib2vChQsXUFFRgZiYGAafG2C2mKGTda4ug4iI2oABSKWEELhw4QIqKysRExOD2NhYV5fk8WzCxh4gIiIPwd/WKnN98ImNjUVcXJyrS/IqPA2eiMgzMACphBACBQUFqK6uRkxMDINPJ1AUBRpJ4+oyiIioDRiAvFxD8KmqqkJcXBzi4+NdXZLXsgkbzwIjIvIQDEBeSgiB/Px8VFdXM/h0FQFIEk+JVgOzzYyjJUdhtpoRbAh2dTlE1A4MQF6mIfjU1NQgLi4O/v7+ri5JNRShMAB5setDj06jw5CIIfDV+rq6LCJqJwYgLyGEQF5eHmpqahAfH8/g4wICgofAvExD6Kmz1UEn65AakcrQQ+QlGIA83PXBJyEhAX5+fq4uSbUUhWeAeYNaay2OlhyFRbFAr9EjtXsqfLQ+ri6LiDoYA5CHEkIgNzcXtbW1DD5uhD1Anqkh9NTZ6mDQGjAkYghDD5GXYwDyMA3Bx2w2IyEhAb6+7I53F4pQeF0oD8LQQ6RuDEAeQlEU5OXlMfi4OQ6Cdm8WmwVHS46ixloDvUbP0EOkYgxAbk5RFOTm5qKuro7Bx80JwYtiuiOrYsWx0mOoslRBK2mRGpEKPx0PGROpHQOQm7o++PTs2RM+Pvwr1d3xNHj3oQgFx0uPw1RngizJGNx9MAL1ga4ui4jcyA2N2FyxYgUkScKiRYvsy4qKijB37lxERkbC398fQ4cOxUcffdTqvl599VX7F/2oUaNw6NChGynNYymKgvPnz+Ps2bOIjo5GcnIyw48HYQByHSEEvr38LfZe2It9hfvQM6gnxsWOw9iYsQw/RNRIu3uA0tPTsWrVKgwaNMhh+bx581BeXo6tW7ciPDwcGzZswOzZs3H48GEMGTKkyX299957WLx4MVauXIlRo0bh5ZdfxtSpU5GVlYWIiIj2luhRru/x6dWrFwwGg6tLIifVKXWosda4ugxVEUIg62oWSqpLAAD9wvqhf3h/F1dFRJ6gXT1AlZWVmDNnDlavXo3Q0FCHdfv378cTTzyBkSNHonfv3vjd736HkJAQZGRkNLu/v//973jooYcwf/589OvXDytXroSfnx/Wrl3bnvI8SsM8PllZWYiKikJycjLDj4fSSlr4aTm2pCtkX83GnoI9+KrwK4QYQjAudhzGxY5DuG+4q0sjIg/RrgC0YMECTJ8+HZMnT260Li0tDe+99x7KysqgKAo2btyI2tpaTJgwocl91dXVISMjw2Ffsixj8uTJOHDgQJOPMZvNMJlMDjdPdOHCBZw5cwbh4eFISUnhAGcPJwRngu5MeaY87CnYgz0Fe2DQGjA+bjzGxY5DpH+kq0sjIg/k9CGwjRs34siRI0hPT29y/fvvv4977rkHYWFh0Gq18PPzw6ZNm5CYmNjk9pcvX4bNZkOPHj0clvfo0QNnzpxp8jHLly/HsmXLnC3dLVx/qCs6OhqxsbGuLok6SIhfCL69+K2ry/AaQgicLjuN0upSAEBcUBzGx413cVVE5C2cCkAFBQVYuHAhduzY0ezA3GeeeQbl5eX44osvEB4ejs2bN2P27Nn46quvMHDgwA4peunSpVi8eLH9vslkQlxcXIfsu7M0BB+LxYKePXvyMJcXigiOgFWxuroMj1djrcHhosOwCRtSuqWgX1g/V5dERF7IqQCUkZGBkpISDB061L7MZrNh7969eOWVV5CVlYVXXnkFJ0+eRP/+9QMRBw8ejK+++gqvvvoqVq5c2Wif4eHh0Gg0KC4udlheXFyMyMimu7YNBoPHBAhFUZCTkwOLxcLBzUQtKKwsxNmys/DR+mB09GjoZJ2rSyIiL+ZUAJo0aRJOnDjhsGz+/PlITk7GkiVLUF1dDaB+DM/1NBpNsxeK1Ov1GDZsGHbu3Ik777wTQH1o2LlzJx5//HFnynMr7PFRJ0XwgqjOEELg+OXjuFp7FVH+UZgYP9HVJRGRSjgVgAIDAzFgwACHZf7+/ggLC8OAAQNgsViQmJiIX/ziF/jb3/6GsLAwbN68GTt27MDHH39sf8ykSZMwc+ZMe8BZvHgx7rvvPgwfPhwjR47Eyy+/jKqqKsyfP78Dmti1Gnp8rFYrgw9RM6ot1ThcfBiKUDAgfAAGdx/s6pKISGU6dCZonU6Hbdu24de//jVuv/12VFZWIjExEevXr8ett95q3+78+fO4fPmy/f4999yD0tJS/P73v0dRURFSU1Oxffv2RgOj3RkPdRHAq8G3JteYixxjDnx1vkiLToNW5mT0ROQakvCCCxiZTCYEBwfDaDQiKCioQ/dtNBpx7tw5xMTEIDIystFMv+zxoeu9d+g93DPyHleX4VasihVHio+gylKFhOAE9A7u7eqSiMhNdOb3d2v451cbxMfHw8fHB+fOnQMA+Pj4IDo6Gnl5eQw+RM24XHMZJ0pPQCNrMKzHMPjr/F1dEhGRHQNQKyRJghACQUFB9nRaU1OD3NxcxMXFMfgQXUcIgZOXT+JyzWWE+YZhQtwEXh+NiNwSA1ArJElqdAabr69vsxM7EqnRDwc1D+zeMXN+ERF1FgagVsiyDC8YJkVdRG2DoL8r/w55pjz46fw4qJmIPAp/W7Wi4RAYEdWzKBYcLjoMs82MXsG9OHcPEXkkBqBWMAAR1SuuKsbpstPQyloM6zEMvlpevJeIPBcDUCuaGgNEpBZCCBwrPQaj2Yjuft0xPnY8BzUTkVdgAGoFxwCRGpnqTDhafBQCAoO7D0aoT6irSyIi6lAMQK3gITBSk7NXz+Ji5UUE6AJwc+zNqhvUTUTqwQDUCgYgcoYnXgzVqliRXpSOWmst+oT2wYS4Ca4uiYio0zEAtYJjgMgZntRjUlZbhmMlx6CRNRjeYzj8dH6uLomIqMswALWCY4DImwghcKrsFEqrSxHqE8qZmolItRiAWsEvB/IGtdZapBelwyZsSOmWgv5h/V1dEhGRSzEAEXmxXGMucow5MGgNGB01GjqNztUlERG5BQYgIi9jUSzIKM6A2WpGXFAcZ2omImoCAxCRlyiqKkJWWRY0sgZDI4ZyUDMRUQsYgIg8mCIUHCs9BpPZhAi/CIyPG+/qkoiIPAIDEJEHMpqNyCzJBACkRqQi2BDs2oKIiDwMAxCRBzlTdgaXKi8h2BDMmZqJiG4AAxCRm6u11uJw8WFYFSuSQpOQHJ/s6pKIiDweAxCRmyqoKMD58vPQy3qMjBwJvUbv6pKIiLwGAxCRG1GEgiPFR1BpqURMQAyvy0VE1EkYgIg6UHsvhlptqcbh4sMQQnBQMxFRF2AAIupAzg5KvlBxAeeunoOvzhdp0WnQyvxIEhF1Bf62JepiDTM111prER0QzZmaiYhcgAGIqItcrLyIs1fPQitrOVMzEZGLMQC1gRDC1SWQh7IpNhwpOYIqSxWi/KM4qJmIyE0wALWBJEmuLoE8zJWaKzhx+QRkSUZqRCqC9EGuLomIiK7DAETUQYQQKKwuxJ6CPQjxCcH42PEMz0REbooBiOgG2Ww25Obmwmq14r4h9yE0KNTVJRERUSsYgIjaqaamBvn5+ZBlGT179oROp3N1SURE1EYMQG3AQdB0vdLSUpSVlcHHxwd9+vSBLPOCpEREnoYBqA04joMURUFeXh7MZjPCw8ORlJTk6pKIiOgGMAARtaC6uhoFBQWQJAnx8fHw8fFxdUlERNQBGICImlBUVASj0cjDXEREXooBiOgaq9VqP5srMjISkZGRri6JiIg6CQMQqV5VVRUKCgqg0Wh4NhcRkUowAJFqXbx4ESaTCf7+/khKSuJgdyIiFWEAIlWxWCzIy8uDzWZDZGQkoqOjXV0SERG5AAMQqUJ5eTmKi4vth7m0Wr71iYjUjN8C5LWEECgoKEBNTQ2Cg4M5dw8REdkxAJHXMZvNyMvLgxACsbGx8Pf3d3VJRETkZhiAyGtcvnwZV65cgV6vR2JiIufuISKiZjEAtQGvBea+Gi5RUVdXh7CwMB7mIiKiNmEAagOeHu1+eIkKIiK6EQxA5FEaLlHh6+uLvn37MpwSEVG7MACR27NarcjLy4PVakVERAQPcxER0Q1jACK3ZTKZcPHiRWi1WiQkJPASFURE1GEYgMitWK1W5Ofnw2KxIDAwkJeoICKiTsEARG6htLQUZWVl0Gg0iI+Ph16vd3VJRETkxW5oopQVK1ZAkiQsWrQIAJCbmwtJkpq8ffDBB83up7KyEo8//jhiY2Ph6+uLfv36YeXKlTdSGnkAq9WK8+fPIysrC7IsIykpCYmJiQw/RETU6drdA5Seno5Vq1Zh0KBB9mVxcXG4dOmSw3ZvvPEGXnjhBUybNq3ZfS1evBhffvkl3n77bfTs2ROff/45HnvsMURHR2PGjBntLZHc1PXX5eLYHiIicoV29QBVVlZizpw5WL16NUJDQ+3LNRoNIiMjHW6bNm3C7NmzERAQ0Oz+9u/fj/vuuw8TJkxAz5498fDDD2Pw4ME4dOhQe8ojN6QoCnJzc5GVlYXa2lp7bw/DDxERuUK7AtCCBQswffp0TJ48ucXtMjIykJmZiQceeKDF7dLS0rB161YUFhZCCIFdu3bh7NmzmDJlSpPbm81mmEwmh1tn4kzQ7VdZWYmsrCxkZ2cjMjISSUlJiIyMdHVZRESkck4fAtu4cSOOHDmC9PT0Vrdds2YNUlJSkJaW1uJ2//znP/Hwww8jNjYWWq0Wsixj9erVGDduXJPbL1++HMuWLXO2dOoiQggUFhaiqqoKfn5+nLCQiIjcjlMBqKCgAAsXLsSOHTtavfRATU0NNmzYgGeeeabV/f7zn//EwYMHsXXrViQkJGDv3r1YsGABoqOjm+xlWrp0KRYvXmy/bzKZEBcX50xTnMIv77apra1Ffn4+hBCIiYlBbGysq0siIiJqkiScOL6zefNmzJw5ExqNxr7MZrNBkiTIsgyz2Wxf9+9//xsPPPAACgsL0b1792b3WVNTg+DgYGzatAnTp0+3L3/wwQdx4cIFbN++vdW6TCYTgoODYTQaERQU1NbmtFl2djYSExM7fL/eori4GOXl5TAYDIiPj+dV2ImIqE06+/u7JU71AE2aNAknTpxwWDZ//nwkJydjyZIlDsFozZo1mDFjRovhBwAsFgssFkujL02NRgNFUZwpr9NwDFBjFosFeXl5sNlsvDwFERF5HKcCUGBgIAYMGOCwzN/fH2FhYQ7Ls7OzsXfvXmzbtq3J/SQnJ2P58uWYOXMmgoKCMH78eDz99NPw9fVFQkIC9uzZg7feegt///vf29Ek6kxlZWUoLS2FVqtFz549odVyLk0iIvI8nfLttXbtWsTGxjZ7FldWVhaMRqP9/saNG7F06VLMmTMHZWVlSEhIwJ///Gc88sgjnVGe09Q+BshmsyE/Px91dXUIDQ1lbw8REXk8p8YAuSuOAeocFRUVuHjxIiRJQkJCAgwGg6tLIiIiL+IxY4DUygsyYpsJIXDhwgVUV1cjICCAp7ATEZFXYgBqo/LycgghOvzWkeGiIai1d59CCCiKgtjY2E6dVoCIiMjVGIDaICEhAUaj0eHirrIsN3vhV2duRERE1PUYgNpAr9e3ejo/EREReQ7OWEdERESqwwBEREREqsMARERERKrDAERERESqwwBEREREqsMARERERKrDAERERESqwwBEREREqsMARERERKrDAERERESqwwBEREREqsMARERERKrDAERERESqwwBEREREqsMARERERKrDAERERESqwwBEREREqsMARERERKrDAERERESqwwBEREREqsMARERERKrDAERERESqwwBEREREqsMARERERKrDAERERESqwwBEREREqsMARERERKrDAERERESqwwBEREREqsMARERERKrDAERERESqwwBEREREqsMARERERKrDAERERESqwwBEREREqsMARERERKrDAERERESqwwBEREREqsMARERERKrDAERERESqwwBEREREqsMARERERKrDAERERESqwwBEREREqsMARERERKrDAERERESqc0MBaMWKFZAkCYsWLQIA5ObmQpKkJm8ffPBBi/s6ffo0ZsyYgeDgYPj7+2PEiBHIz8+/kfKIiIiImtTuAJSeno5Vq1Zh0KBB9mVxcXG4dOmSw23ZsmUICAjAtGnTmt3X+fPnMXbsWCQnJ2P37t04fvw4nnnmGfj4+LS3PCIiIqJmadvzoMrKSsyZMwerV6/Gc889Z1+u0WgQGRnpsO2mTZswe/ZsBAQENLu/3/72t7j11lvx/PPP25fddNNN7SmNiIiIqFXt6gFasGABpk+fjsmTJ7e4XUZGBjIzM/HAAw80u42iKPjkk0/Qt29fTJ06FRERERg1ahQ2b97c7GPMZjNMJpPDjYiIiKitnA5AGzduxJEjR7B8+fJWt12zZg1SUlKQlpbW7DYlJSWorKzEihUrcMstt+Dzzz/HzJkzcdddd2HPnj1NPmb58uUIDg623+Li4pxtBhEREamYUwGooKAACxcuxDvvvNPq+Jyamhps2LChxd4foL4HCADuuOMO/PKXv0Rqaip+/etf47bbbsPKlSubfMzSpUthNBrtt4KCAmeaQURERCrn1BigjIwMlJSUYOjQofZlNpsNe/fuxSuvvAKz2QyNRgMA+PDDD1FdXY158+a1uM/w8HBotVr069fPYXlKSgr27dvX5GMMBgMMBoMzpRMRERHZORWAJk2ahBMnTjgsmz9/PpKTk7FkyRJ7+AHqD3/NmDED3bt3b3Gfer0eI0aMQFZWlsPys2fPIiEhwZnyiIiIiNrEqQAUGBiIAQMGOCzz9/dHWFiYw/Ls7Gzs3bsX27Zta3I/ycnJWL58OWbOnAkAePrpp3HPPfdg3LhxmDhxIrZv347//ve/2L17t5PNISIiImpdp8wEvXbtWsTGxmLKlClNrs/KyoLRaLTfnzlzJlauXInnn38eAwcOxL/+9S989NFHGDt2bGeUR0RERConCSGEq4u4USaTCcHBwTAajQgKCnJ1OURERNQGrvz+5rXAiIiISHUYgIiIiEh1GICIiIhIdRiAiIiISHUYgIiIiEh1GICIiIhIdRiAiIiISHUYgIiIiEh1GICIiIhIdRiAiIiISHUYgIiIiEh1GICIiIhIdRiAiIiISHUYgIiIiEh1GICIiIhIdRiAiIiISHUYgIiIiEh1GICIiIhIdRiAiIiISHUYgIiIiEh1GICIiIhIdRiAiIiISHUYgIiIiEh1GICIiIhIdbSuLoCIiOhG/OnjU/j3wTxIACSpfpkECZKEa8skSPULv7//g3XStQ2+X954H2hY3sS6RvsHEB5gwJOT+mDMTWFd+NOgtmIAIiIij3aupBI3dQ/APcNjIQAIgWv/CsB+X1y3/Pv7uLZdU+vEtQc3tbzhPq57rh+uO5J3FfeuPogp/Xpg6a0p6BXu3+U/G2oeAxAREXk0IQR6hfvh5z/q5epSHCiKwH+PX8Tz27Pwk7/vwbwxPfHkpESE+OldXRqBY4CIiMgLXDsI5VZkWcIdqTHY+dR4/PInffFeej7Gv7Aba/floM6quLo81WMPEBERuZSiKCg2FiHn0rcoLD0GRVgRHZ6KkIDu6BYUAWPFFUSERuPgqU9gUyzQ6/yR1m86An2DIMvu/3e8j06DBRMTMXt4HP6+4yye+6R+zNLSacn4Sb8e9vFF1LUk0XCQ1IOZTCYEBwfDaDQiKCjI1eUQEalSaXkxzhedgk5rgNVmRkHxUQihoM5SDtQeQZjhO1wxj4RWMUKWzNBK1dBqqqDXVkGrsTj9fFabFjbFALPVB+fNd+P/7vpVxzeqE5wpMuHPn5zGV+cuY3Tvbvjd9H4YEBPs6rJcwpXf3+wBIiKiG/LOtscQIu+Hj77CYXmIkGBVdLBYAuDnVwYA0CpXYZWCoMjhgCYAGm0wdLpgBPpHI657MuK698ZlYzFsig1Xq0phqixFeWUefPQhCAqIQlJMKs5fOomrFRdRXXsFNqUW3XVrMDw4yxVNb5fkyCC8df9I7D5bij9/chq3v7IPs4bG4umpSegR5OPq8lSDAYiIiNrFZrOhsCwfIfJ+1AotjMpc6HQBCPSPQfeQBKTEpcLP4Of0foP8GnpDUppc3yM0yuH+kUNnoNF41teZJEmYmBSBmxPD8W56AV7acRafHL+EX4zvjYfH9Yaf3rPa44n4EyYiUrG6mmrIWh3qFAtO5R9F4ckc2MKvosp0HMHyEfgbygEAZTUxUJQg+GkvocYaAQ0sCPTNh0a2wUcPWH2WYFbawy5pgyRpIIRnDirWamTMHZ2AO1Kj8equbLy26zw2HirA01OTMHNIDGSZ44M6CwMQEZEKVNZU4nJFCXKKvkXxlePQanxRU3EaBkshtJpq+BpKodfWIiAYUMwyIKJQqwRAtpih09TBpoTBJvniqtQbGpTALAfCpp2KsOCbENu9L/pE93NZ2yTIgIcGoAZBPjosnZaCn41KwIrtZ/DUB8ewbn8Ofje9H0b35kSKnYEBiIjIS9hsNpRXXcXpgiOoNVegts6E8vITCLAdhL+hFLJcHxK6A1DqZEgiDrWaSJi1CTBrJqJP3GREhEQjIjgKPnoPGosiSRDC5uoqOkRcNz+8+tOhmJ9Whj99chr/+8ZBTO3fA7+exokUOxoDEBGRB7psKsHBU5/g6tV0aHRhsJkvIUz7DQy6agD1l2TwBQAE4SqGoFaejtCgmxDfoz/6RvdDna0OvnpfF7ag4whhhSTpXF1Ghxresxs2PZqG/x6/iL9+egZTXro2keKP+yDYz7va6ioMQEREHmTz16/DXLYJ3fy+g68koIhu0CnVqBFhuIpbEeLfD9HhSYgIjsHJzFNY9eoryMjYjkuXLmHTpk1IGT4QAOCr8W12/pnnn38eTz/9NHbv3o2JEyc2uc2hQ4cwYsQI1NbW4pFHHkFGRgZOnz6N2267DZs3b+6s5jdJKDbIOu8Ic9drmEhxav9IrNmXg9d2ZePdQ/kI9dNDq5GgkSXoZBkaWWr2vlaWoZUlaDQStM3dtz9Wgua6+9prN41GhkEjY+qASAT7ek/4YgAiInJDFmsdTuYdRWHpKZRf3oEePumoquuGQJ/LCPQHTIanMLTPLUiI6N3sPo5bTmLw4MG4//77cddddzVaf+nSJYf7n376KR544AHMmjULAJCWltZom2eeeQY7d+7E8OHDAdQfdvP19cWTTz6Jjz766Eab3S6KsEAne88X8w81TKT4P8Nj8WHGBVSbbbAqAjZFgcUmYFMErIqA1abY/9+mCFiu3a+xKLCZv7//w/XXP97awv0aiw33pfV09Y+jwzAAERG5oU2f3o4w/2z4AtAZdCgzR0MIH1TWDMBt4/+GkIDQVvcxbdo0TJs2rdn1kZGRDve3bNmCiRMnonfv+lCl1+sdtrFYLNiyZQueeOIJe++Rv78/Xn/9dQDA119/jfLycidbeuOEYoMke//XWUSgDx6bkOiS50599nNU13nHOKsG3v+OISLyQDXamwBko3f/z9CrR+d/6RUXF+OTTz7B+vXrm91m69atuHLlCubPn9/p9ThDCAtkFQQgV9JpZK+7fpn7X0SFiEiFZKUGlbXhXRJ+AGD9+vUIDAxs8lBZgzVr1mDq1KmIjY3tkpraSgh19AC5kl4jo87GHiAiIuok1eZqfLhzMWJ898KoW9Qlz2mxXMXK11dg6pQYnD29GI0vESlQXFyJzz7bjueXT8KxjF80uZ+yK/tRUVGHzIyHAYd9/GB/160TaGG76+6LFvZXU5eLYHlokzVRxzBova8HiAGIiMhNnC44gRPHFiHScAGVhl/hrh81HTQ62mefvYOc3Kv407PDYK277npe150ktmnzSQQH6zF2bA/YbDUOK+1nkwkFEAqEcv2FTa/b7vodXnvM98sar2v0mB+6tl1oyFj06HFrS02kGyTLEmzelX8YgIiIXO2bL/+NmnN/guUmAZ0chu6912PITaO77Pnffvtj9O2rx92z34HBENFovRACn/3vTbj//scxKu1vze6nW/jPIWvLMWTEus4sl1zAYlOg13rXqBkGICKiLlZ91Yisvem4dPAw9Ie/QkzBdwjUyti74l7M+8nT7bqAaFMqKyuRnZ1tv5+Tk4PMzEx069YN8fHxAACTyYT//nc3Hno4CJKkaXI/X375JXJycvDggw82uf7UqVOoq6tDWVkZKioqkJmZCQBITU3tkHaQ69VZFeg13nVdMgYgIqJOYLVYcebQCVw8cgKVF4thLr0MXelFRBWdR6jxKnwARGt1uBwVh8rhN8E/IxuP3PaHDq3h8OHDDhMZLl68GABw33334c033wQAbNy4EUIAEycGNDub8po1a5CWlobk5OQm1996663Iy8uz3x8yZAiAH47bIU9WZ2UPEBERtaDwuwvIfO4FRB3eA986M+IAWDQa1Pn5oS4wGJUDhqOq32BEjh6GfiMHQK/TImfV/6H28PkOr2XChAmthpCHH34YM+6IwrffLmq2B2jDhg0t7iM3N7e9JZKHYAAiIqImCSHw9f9bC/9//T9ESRIupE1F1C2TkXLzcASEtTJpYTOXpLgRtrpaQCjQtOFwWsOFRDmXDrWkxQHpHojvdiKiG1RrqkDOyJEIA3Bm4BiM/8cKDI1uPJi4OZKu/tDTqUHJgAaALNX/q5EAjQTp2r/QyIBWgpAA1NkAqwCsyrV/Uf+vDYAVkIQEoRfo/eVn8AlPaPH5hWKtr0PiVwI1TaORYFW865DmDb3bV6xYgaVLl2LhwoV4+eWXkZubi169ejW57fvvv4//+Z//aXWfjzzyCFatWoWXXnoJixYtupHyiIg63dH8q3huUyaeA1CeMhh3vr+m2YuMNifqzidQaDZD1FRDsVogLNduVguExQpcu486C2C1QlIkwMcAGPSQfPSQ9HpIegNkvR6SwQBJb4Cl8AKUD46jtiSv9QAkrACkZg+BEWllCVYvOw++3QEoPT0dq1atwqBBg+zL4uLiGl0474033sALL7zQ4vVoGmzatAkHDx5EdHR0e8siIuoS33x3Bf/8Mhv7si8jMSIAAJD801lOhx8AMIRGofcjL3ZofaX7PsTlD45DqatudVshrJDA8EPN08qy1/UAtWtEU2VlJebMmYPVq1cjNPT7Y9sajQaRkZEOt02bNmH27NkICAhocZ+FhYV44okn8M4770Cn896r+hKR57IpAl+cKsb/vnEA97xxEFeq6vDanKH4fNE4V5fWiMbgCwBQ6mpa3VYIK3t/qEUaWYLNywJQu3qAFixYgOnTp2Py5Ml47rnnmt0uIyMDmZmZePXVV1vcn6IomDt3Lp5++mn079+/PSUREXUaY40FH2ZcwPr9ucgvq0ZqXAhW/mwopvaPbFePT1eQ9fUByNaWAAQBsAeIWqDVSLAo3nUIzOkeoI0bN+LIkSNYvnx5q9uuWbMGKSkpSEtLa3G7v/71r9BqtXjyySfbVIPZbIbJZHK4ERF1JEURSM8twxPvHsWwP+3Aik9PY2h8CDY9lobNC36EWwZENQo/+0+dwu23347o6GhIkoTNmzc7rJckqcnbCy+8AADYvXt3s9ukp6fbt7njjjsQFRUFf39/pKam4p133mlUv3zt7C9RZ25ji73rr3vqWFpZgs3mXe8RpwJQQUEBFi5ciHfeeQc+Pj4tbltTU4MNGzbggQceaHG7jIwM/OMf/8Cbb77Z5r+kli9fjuDgYPstLi6uzW0gIvqhhrlyFEXgTJEJf/ssC+Ne2IX/WXkAxwrK8etpyfh6yY/x8v8OwZD4xqe0Nzy+ymzG4MGDm+31vnTpksNt7dq1kCQJs2bNAgCkpaU12ubBBx9Er169MHz4cADA/v37MWjQIHz00Uc4fvw45s+fj3nz5uHjjz92fLJrQwmExdrWn0KLa1esWAFJkhxOTnnjjTcwYcIEBAUFQZIklJeXt/G5yNN44xggpw6BZWRkoKSkBEOHfn/VXZvNhr179+KVV16B2WyGRlPfjfrhhx+iuroa8+bNa3GfX331FUpKSuzTsjfs86mnnrKfWfZDS5cutc9oCtRP5c4QRETO2pJZiIUbMwEAYf56VNfZUGOxIchHi+mDonBnagxG9OwGWW7bH2dThg7F7LvvbnZ9ZGSk4/Nv2YKJEyeid+/eAAC9Xu+wjcViwZYtW/DEE0/Y/0D8zW9+47CPhQsX4vPPP8d//vMf3Hbbbfblkvbar/c2BKD6+V2a/3Jr6qQXAKiursYtt9yCW265BUuXLm31eejGCCFQabZCp5Gh08jQtPF92RE0sgSrlx0CcyoATZo0CSdOnHBYNn/+fCQnJ2PJkiX28APUH/6aMWMGunfv3uI+586di8mTJzssmzp1KubOnYv58+c3+RiDwQCDweBM6UREDt49lI+l/6n/ffaL8b2h18gI9tUhKTIQI3p2g4+uc8fEFBcX45NPPsH69eub3Wbr1q24cuVKs78LGxiNRqSkpDgsawhAwmJrW0HN5J/rT3r54ZjPht6g3bt3t+05qM1KKmqRmV+OcyWVOF9SifOllThfWoVK8/eBVpYAnUaGXitDfy0U6bSS/f8dl8vQayTotbI9QOk0MgxaGTqNZL///WOka4+pX1Zptqp7EHRgYCAGDBjgsMzf3x9hYWEOy7Ozs7F3715s27atyf0kJydj+fLlmDlzJsLCwhAWFuawXqfTITIyEklJSc6UR0TUooKyanydfRlbj13E/vNXMG9MAv5we/8u/Uu6wfr16xEYGIi77rqr2W3WrFmDqVOnIjY2ttlt3n//fXsPjaNrX1ZtalrzG7X1pBdqP5sikFVUgYz8qziSdxUZeVeRX1Y/fUGQjxaJEQHo2yMQ0wZGITrEF4oiUGdTYLEpqLPW/2uxCdRZlfrl15bVXVtmsX1/q6i12rdveHzDvixWYX98na3+dv2VVG73j3LRT6hzdMq0n2vXrkVsbCymTJnS5PqsrCwYjcbOeGoiokbMVhuW/fcUNnyTD0kCRvXqhtfmDMWtA133C33t2rWYM2dOs+MpL1y4gM8++wzvv/9+s/vYtWsX5s+fj9WrVzc6g1Zc+2td0rRhqKckXTsTzFHDSS8NA7CpYxhrLMgsKEdGXn3gOZp/FVV1NmhlCf1jgjE5pQeGJYRiaEIIIoN8XHqmobUhXNkUBPl410zhN9yapro+//KXv+Avf/lLs49p7eJ8vLAeEXWUT09cwq//cwLVdVb84fZ+uGtoLIJ9XTvX2FdffYWsrCy89957zW6zbt06hIWFYcaMGU2u37NnD26//Xa89NJLTY+1bBiv0eYvT8ffyw0nvezYsaPVk17cndWmoLTSjCJjLYqMtSirroPFqsCqCChCICUqqNMOewohkHulGhnXenaO5F3F2ZIKCAF089djaHwoHv9xHwxLCMWg2OBOP/TqLK1GhlYD+HrhNAneFeeIiK4pLK/BK19m491D+ZjSrwd+dUuyfcbmDtfKH3U/tGbNGgwbNgyDBw9uZncC69atw7x585qcGHb37t247bbb8Ne//hUPP/xwyzXJbTnZt/EgaGdOenGlSrMVRcZaFJvqw02Rqf7/L1237HKlGdcPX5Eaxs5oZAghUFVng0ErY0TPbhjbJxw39wlHSmRQmwe/X6/WYsPxC8bvA0/+VZRV1UGSgL4RgRiaEIqHxvXGsIRQ9Azzc9t5pNSAAYiIvEaJqRYbDuVDliSs2nMeAPCnOwfgZ6Piu+SLprK2FrmZmfb7OTk5yMzMRLdu3exnuppMJnzwwQd48cXmL33x5ZdfIicnBw8++GCjdbt27cJtt92GhQsXYtasWSgqKkJ51j6U/f63CBFyfY5RANiujexpyyEwCAhYUWsugo+h/iw0Z056cQUhBKa8tBfnSiodlof46RAZ5IMeQT5IiQzCxKQIRAb72JdFBvsg1E9nfz8IIZBVXIF95y7jq3OX8fIXZ7Hi0zMI89fjR4nh9kAUFezbZB1Fxlp72MnIv4pvC42wKgL+eg2GxIfiZ6MTMCwhFKlxIS7veSRHDEBE5BU+zLiAX314zP6X/tzRCfjVLUkI9Om6L53M8+dx+9y59vsN03Xcd999ePPNNwHUj6sRQuDee+9tdj9r1qxBWloakpOTG61bv349qqursXz5cocJaUf4+uLfv5gKydcASICQAdnHgLAxd7Zat7/fTQAAc+0lewBqy0kvRUVFKCoqQnZ2NgDgxIkTCAwMRHx8PLp169bq894ISZJw19BYPP/ZGcSE+OKVnw5FcmSg04eQJElCcmQQkiOD8ODNvWG22pCRdxX7zl3GvuzL+O/xixACuKm7P8YmhmN07zCUVJjtoaewvH6m7bhuvhgWH4q7h8ZgaEIoknoEQtum8EmuIonWBuR4AJPJhODgYBiNRgQFBbm6HCLqYl9nX8bP1nyDqf0i8fiPE9GnRwAM2q7roRCKgjP9+iPqz88h5Nqkhl2p4P0VqPz9evT6egd8wpo/Y6w5FRXf4lD6DIwYvglBQYOa3W7ChAlITU3Fyy+/DAD44x//iGXLljXabt26dfj5z3/udB3tsedsKRZuPIoAgxYrfzYMA2KCO3T/V6vqsP/8FezLLsVX5y7jwtUa6DUyBsQEYVhCaP1g5fhQRAR59jgpV3Hl9zd7gIjIo1XUWrD4/UwMjQ/Fa3OGtmvchqcT1wY8S+08LCVE/VxBktRyb9kPT3r54x//iD/+8Y/tes6OMr5vd/z38bF47J0jmPX6fvzpzgGYPbzjJsYN9ddj+qAoTB8UBSEEiky1CPXTu91gZXIe++eIyKP9fcdZmGqs+Oe9Q1QZfgDYz/iS5PYGoPrJ9Tz1ivBx3fzwwSNjMHNIDH714XEs/c8JmK1tnADSCZIkISrYl+HHS7AHiIg81rYTl7Du61z85tZkRIc0PUi1S7h6JIFyrQennQFIsfcAee5Xgo9OgxWzBmFIfAiWfHQCIX46LLml8RgqogbsASIij7QlsxCLNmZixuBoPHRzb1eXc41reqAaJj2E3L4A09ADJLfz8e4k8trZWqN7h7WyJamd57/biUhVrDYFL31xFq/uOo+7hsRgxaxBnEvlWg+Q3N5DYErDITDP/koQQuAfX5xFalwIxvUJd3U55OY8+91ORKpSUWvBI29n4MD5K/jVLUl4dPxNDD8AIK7N+qzSMUAN9mVfxpH8cqybP4LvC2oVAxAReYSL5TVY9F4mTl004e0HRyHtJv6F3+D763619xCY548Bqu/9OYfBscGY0Le7q8shD+C573YiUo0TF4yYu/Yb+Oo0eOWnQxh+fuhagEE7e3C8IQDtP38Fh/OuYu3Ph7P3h9rEc9/tRKQKxmoLHn0nA3Ghfvj3AyMR4qd3dUlup2EeILlN1/1q4vEefgisofdnUGwwJiZFuLoc8hA8C4yI3JYQAk99cAymGgtemzPUfcNPw2nwrup5UASE1P5T8b8PQJ75N/GB767gUG4ZnvxxH/b+UJt55rudiFRh9Vff4YvTxfjXvOGI6+bn6nLclhAKIAHfHn/qWgiTrgWB+qu8K4oViq0OQrFAKFYowgJFsUAIK4RiQZ2tDIDn9gD944tzGBAThEkp7P2htmMAIiK3dLG8Bs9vz8IvxvXG5H49XF2OW/PVR8MsSaiqzIWAYu+REhCQIEGSdZAkLWRZC0nSQaPxhVYXVH9fo0OgrIefX0/Isuddrfzgd1fwTU4Z3pg7jL0/5BQGICJyS+8eyoePToMnJ/VxdSluz6CPhKTRYUTaR64upUvlXq7C89vPoF9UEH7CkExOYgAiIrdjtSnYmF6AmUNi4G/gr6lWCcV144+6WN6VKnxy4hI+OX4J3140wU+vwRtzeeYXOY+/WYjI7ew9V4rSCjPuGdFxV/XuCuZz51C1f3+btlVqa2EzmaBUVEKpqgIASFoNIGsgaeT6SQ01MiSN1n7fvl6rAWS5/urvGg3M2echefGFYBtCz7YTl3Cy0ARfnQY/TonA4xMTMSEpAr56zxy7RK7FAEREbsVYbcFLO86hf3QQ+kcHubqctpFlaIIDUbZuHcrWrXPqoZJOC9nXAECqP51dUa79K+r/tSltutiqLtK7Jv/Lv1Jd39Nz4uL3oSc5Ao9NSMSEpO7w0/Pri24M30FE5DYuGWtwz6qDMNVa8Ob8kR5zWEOSZSTu2QtbeTlgs7W6vRCA7OsDOTAQsr71U/uFEIDNBmGzOf6rKBBWK6Ao0AQGdkBLXO/C1Wosfu8YDuWWwUcn48fJEXh0fCImJjP0UMfiu4mI3EKtxYZf/DsDNkXgv4+P9bjT3mUfH8iRkZ2yb0mSAK0Wkta7f2Wn55bhkX9nwFevwT/vHYJJKREMPdRp+M4iIpcTQuA3/zmBs8UV+PCRNI8LP3Tj3j2Uj99vOYlhCaF4bc4wdPN300kvyWswABGRSwkh8PIX5/Cfo4X4x/+mYkBMsKtLoi5ksSl47uNTWH8gD3NHJ+D3t/eDTsOLFFDnYwAiIpdRFIG/bj+DVXu/w69uScIdqTGuLom60NWqOizYcASHcsrw3J0D8LPRCa4uiVSEAYiIXKLKbMXi9zPx+aliPHNbPzwwtperS6IudLa4Ag+9dRimGgvefnAURvcOc3VJpDIMQETU5QrLa/Dg+sPIv1KFN+YO5yy+KqIoAp+eLMKSj44jNtQXbz8wimO+yCUYgIioS524YMT8N9NxudKMuaMTUGyqxdsH8+zrmzrzXYJzp8MLtDxvjhD1Y4/Etf9XhKhfhmvLRf0+6td9//+4tr6+zvqaZEmCJAE6jYxZQ2Pc94r1LlZRa8FHGRfw1oE8fHe5Crf0j8SLswdzpm9yGb7ziKhL7ThdjPLqOmhlCe8eyrcvby6yiCYmARSAk5GoMVmSIEsSUP+fPcg0/L99uVwfvyRJQv1ky/VXWHcITADKqy0INGgx28Nmr+5s2SUVeOtAHj7KuACzVcEtAyLx17sHYXhCqMfM80TeiQGIiLrU4p/0xeKf9HV1GR2u568/ga0NMzargU0R2Hm6GOsP5OLr7CsIDzDggZt746cj4xEZ7OPq8ogAMAAREXUYteefq1V12JhegLcP5qGwvAZD4kPwj/9NxbQBUdBreWo7uRcGICKiDiBJrY898lZniyuweu932HrsIgSAGYOjMW9MAgbFhri6NKJmMQAREXUANY5mOZp/Fa/tPo8dp4oRFeyDhZP74J7hcQgLMLi6NKJWMQAREXUQNRwCE0JgX/ZlvLbrPA58dwW9u/vjhbsH4Y7UGB7mIo/CAERE1AEkSfLqA2CKIvD5qSK8tvs8jl8wYmBMMF6fMxRT+kdCI6ux/4s8HQMQEVEHkACv7AKy2BRsPlqIlXvO43xpFUb37oa37h+Jm/uE8zR28mgMQEREHaB+ELT3qKmz4b30fKz+KgeF5TWYnBKB5+8ejGEJoa4ujahDMAAREXUACZJXdAAZayz494FcrPs6F1er6zBjcDTWTBiO5MggV5dG1KEYgIiIOoLU9KzVnsJYbcHre87j7YN5qLMp+J9hsfjFuJsQH8brdJF3YgAiIuoA9RfI8EyF5TWYt+YbFBlr8bPRCXhgbC9EBHHGZvJuDEBERB1AkjxzDHRWUQXmrf0Geq2Mj5+8Gb3C/V1dElGXYAAiIuoAsiRB8bAEdCinDA+uT0dMqB/W3z8CEYHs9SH1YAAiIuoAsoedEv75t0V44t2jGBIfgjfmDUeQj87VJRF1KQYgIqIOIEnwiB4gIQTeOpCHZf/9FrcMiMRL96TCoNW4uiyiLscARETUAeoPgbm6ipZZbAr+uPVbvPNNPh4Y2wu/uTWFsziTajEAERF1ANnNe4DKq+vw2DtHcCinDH+dNRD3jIh3dUlELsUARETUAWTJfSdCzC6pxIPr02GsseDtB0dhdO8wV5dE5HIMQEREHUCSJLecCHHv2VIs2HAEkUE+2LJgLCc2JLqGAYiIqAPUHwJzdRXfaxjs/OzHp3Bzn3D8894hCOSZXkR2DEBERB3AneYB4mBnotbJN/LgFStWQJIkLFq0CACQm5sLSZKavH3wwQdN7sNisWDJkiUYOHAg/P39ER0djXnz5uHixYs3UhoRUZdylx6g8uo63Lf2EN5LL8BfZw3EM7f1Y/ghakK7A1B6ejpWrVqFQYMG2ZfFxcXh0qVLDrdly5YhICAA06ZNa3I/1dXVOHLkCJ555hkcOXIE//nPf5CVlYUZM2a0tzQioi7nDmOAsksqceerX+P0JRPefnAUz/QiakG7DoFVVlZizpw5WL16NZ577jn7co1Gg8jISIdtN23ahNmzZyMgIKDJfQUHB2PHjh0Oy1555RWMHDkS+fn5iI/nB5iI3J8su/Y0eA52JnJOuwLQggULMH36dEyePNkhAP1QRkYGMjMz8eqrrzq1f6PRCEmSEBIS0uR6s9kMs9lsv28ymZzaPxFRR5MlCYVXa3Aop6zZbVq7WkZLq1t6bEbeVfx1exYHOxM5wekAtHHjRhw5cgTp6emtbrtmzRqkpKQgLS2tzfuvra3FkiVLcO+99yIoKKjJbZYvX45ly5a1eZ9ERJ0txFeHzZkXsTnTNeMXOdiZyDlOBaCCggIsXLgQO3bsgI9Py1cNrqmpwYYNG/DMM8+0ef8WiwWzZ8+GEAKvv/56s9stXboUixcvtt83mUyIi4tr8/MQEXW0dx4ajRJTbbPrWzs41vLRs5YfbdBqENeNh7yInOFUAMrIyEBJSQmGDh1qX2az2bB371688sorMJvN0GjqL6r34Ycforq6GvPmzWvTvhvCT15eHr788stme38AwGAwwGAwOFM6EVGnCjBoEdC96bGOROR+nApAkyZNwokTJxyWzZ8/H8nJyViyZIk9/AD1h79mzJiB7t27t7rfhvBz7tw57Nq1C2FhnKadiIiIOo9TASgwMBADBgxwWObv74+wsDCH5dnZ2di7dy+2bdvW5H6Sk5OxfPlyzJw5ExaLBXfffTeOHDmCjz/+GDabDUVFRQCAbt26Qa/XO9smIiIiohZ1ykzQa9euRWxsLKZMmdLk+qysLBiNRgBAYWEhtm7dCgBITU112G7Xrl2YMGFCZ5RIREREKiYJV8/c1QFMJhOCg4NhNBpbHDtERERE7sOV3983dCkMIiIiIk/EAERERESqwwBEREREqsMARERERKrDAERERESqwwBEREREqsMARERERKrDAERERESqwwBEREREqtMpl8Loag2TWZtMJhdXQkRERG3V8L3tiotSeEUAqqioAADExcW5uBIiIiJyVkVFBYKDg7v0Ob3iWmCKouDixYsIDAyEJEmuLueGmEwmxMXFoaCgQFXXNVNruwG2nW1n29WEbXdsuxACFRUViI6Ohix37agcr+gBkmUZsbGxri6jQwUFBanuwwGot90A2862qw/bzrYD6PKenwYcBE1ERESqwwBEREREqsMA5GYMBgP+8Ic/wGAwuLqULqXWdgNsO9vOtqsJ2+4+bfeKQdBEREREzmAPEBEREakOAxARERGpDgMQERERqQ4DEBEREakOA1AnOnv2LO644w6Eh4cjKCgIY8eOxa5duxy22blzJ9LS0hAYGIjIyEgsWbIEVqu12X2WlZXhiSeeQFJSEnx9fREfH48nn3wSRqPRYTtJkhrdNm7c2CntbEpntB0AamtrsWDBAoSFhSEgIACzZs1CcXGxwzb5+fmYPn06/Pz8EBERgaeffrrV/XaktrQ9PT0dkyZNQkhICEJDQzF16lQcO3as2X3m5uY2+ZpKkoQPPvjAvp0nvO7Oth0AJkyY0KhdjzzyiMM23vi6e9PnvT2vuzd83t98881mP7slJSVN7nP37t3NPiY9PR1A878TDh486LHtBoCePXs22n7FihUO2xw/fhw333wzfHx8EBcXh+eff759jRDUafr06SNuvfVWcezYMXH27Fnx2GOPCT8/P3Hp0iUhhBCZmZlCr9eLZcuWiXPnzondu3eL5ORk8dRTTzW7zxMnToi77rpLbN26VWRnZ4udO3eKPn36iFmzZjlsB0CsW7dOXLp0yX6rqanp1PZerzPaLoQQjzzyiIiLixM7d+4Uhw8fFqNHjxZpaWn29VarVQwYMEBMnjxZHD16VGzbtk2Eh4eLpUuXdmp7r9da2ysqKkS3bt3Ez3/+c3HmzBlx8uRJMWvWLNGjRw9RV1fX5D6tVqvDa3np0iWxbNkyERAQICoqKuzbufvr3p62CyHE+PHjxUMPPeTQLqPRaF/vra+7t3ze2/u6e8Pnvbq6utFnd+rUqWL8+PHN7tNsNjd6zIMPPih69eolFEURQgiRk5MjAIgvvvjCYbuWfp4dqTPaLYQQCQkJ4tlnn3V4XGVlpX290WgUPXr0EHPmzBEnT54U7777rvD19RWrVq1yug0MQJ2ktLRUABB79+61LzOZTAKA2LFjhxBCiKVLl4rhw4c7PG7r1q3Cx8dHmEymNj/X+++/L/R6vbBYLPZlAMSmTZturBHt1FltLy8vFzqdTnzwwQf2ZadPnxYAxIEDB4QQQmzbtk3IsiyKiors27z++usiKChImM3mDmtjc9rS9vT0dAFA5Ofn27c5fvy4ACDOnTvX5udKTU0V999/v8Myd3/d29v28ePHi4ULFza7Xk2vuyd+3tvTdm/5vP9QSUmJ0Ol04q233mrz89TV1Ynu3buLZ5991r6sIQAdPXq03fW3V2e2OyEhQbz00kvNrn/ttddEaGiow+u7ZMkSkZSU5FwjhBA8BNZJwsLCkJSUhLfeegtVVVWwWq1YtWoVIiIiMGzYMACA2WyGj4+Pw+N8fX1RW1uLjIyMNj+X0WhEUFAQtFrHS7stWLAA4eHhGDlyJNauXQvRRVM+dVbbMzIyYLFYMHnyZPuy5ORkxMfH48CBAwCAAwcOYODAgejRo4d9m6lTp8JkMuHbb7/t6KY20pa2JyUlISwsDGvWrEFdXR1qamqwZs0apKSkoGfPnm16noyMDGRmZuKBBx5otM6dX/cbafs777yD8PBwDBgwAEuXLkV1dbV9nVped8AzP+/tabu3fN5/6K233oKfnx/uvvvuNj/P1q1bceXKFcyfP7/RuhkzZiAiIgJjx47F1q1b290WZ3R2u1esWIGwsDAMGTIEL7zwgsMhzQMHDmDcuHHQ6/X2ZVOnTkVWVhauXr3qXEOcjkzUZgUFBWLYsGFCkiSh0WhEVFSUOHLkiH39Z599JmRZFhs2bBBWq1VcuHBB3HzzzQKA2LBhQ5ueo7S0VMTHx4vf/OY3DsufffZZsW/fPnHkyBGxYsUKYTAYxD/+8Y8ObV9LOqPt77zzjtDr9Y2WjxgxQvzqV78SQgjx0EMPiSlTpjisr6qqEgDEtm3bOrCFzWut7ULUH9q46aabhCzLQpZlkZSUJHJzc9v8HI8++qhISUlptNzdX3ch2tf2VatWie3bt4vjx4+Lt99+W8TExIiZM2fa16vldffUz7sQzrfdmz7v10tJSRGPPvqoU88xbdo0MW3aNIdlpaWl4sUXXxQHDx4Uhw4dEkuWLBGSJIktW7a0qx3O6qx2v/jii2LXrl3i2LFj4vXXXxchISHil7/8pX39T37yE/Hwww87PObbb78VAMSpU6ecagMDkJOWLFkiALR4O336tFAURcyYMUNMmzZN7Nu3T2RkZIhHH31UxMTEiIsXL9r39+KLL4qgoCCh0WiEn5+fWL58uQAgNm7c2GotRqNRjBw5Utxyyy2tHvd95plnRGxsrEe33ZW/EDuy7dXV1WLkyJFi3rx54tChQ+LAgQNi1qxZon///qK6urrVWqqrq0VwcLD429/+1uq27va632jbG+zcuVMAENnZ2UIIdbzunvx5b0/bveXzfr39+/cLAOLw4cNtrqWgoEDIsiw+/PDDVredO3euGDt2rFNtvZ47tbvBmjVrhFarFbW1tUIIBiCXKikpEadPn27xZjabxRdffCFkWXYYqCmEEImJiWL58uUOyxRFEYWFhaK6ulqcOnVKABCHDh1qsQ6TySTGjBkjJk2a1KbBjh9//LEAYH8TtYer297wpXf16lWH5fHx8eLvf/+7EKL+F//gwYMd1n/33XcCQIt/nXRl2//1r3+JiIgIYbPZ7OvNZrPw8/MT7777bqu1vPXWW0Kn04mSkpJWt3W31/1G296gsrJSABDbt28XQnj/6+7pn/f2tN1bPu/Xu//++0VqaqpTtTz77LOie/fubRrc/Morr4jIyEin9n89d2p3g5MnTwoA4syZM0KI+pB3xx13OGzz5ZdfCgCirKzMqX07HkSmVnXv3h3du3dvdbuG8Qmy7DjMSpZlKIrisEySJERHRwMA3n33XcTFxWHo0KHN7ttkMmHq1KkwGAzYunVro7E0TcnMzERoaOgNXYTO1W0fNmwYdDoddu7ciVmzZgEAsrKykJ+fjzFjxgAAxowZgz//+c8oKSlBREQEAGDHjh0ICgpCv379nGito45se3V1NWRZhiRJDuslSWr082nKmjVrMGPGjDbV426v+422vUFmZiYAICoqCoB3v+7e8HlvT9u95fPeoLKyEu+//z6WL1/e5jqEEFi3bh3mzZsHnU7X6vaZmZn2z0R7uEu7r5eZmQlZlu2v75gxY/Db3/4WFovF/jPZsWMHkpKSEBoa6tzO2xXJqFWlpaUiLCxM3HXXXSIzM1NkZWWJ//u//xM6nU5kZmbat3v++efF8ePHxcmTJ8Wzzz4rdDqdw9kcFy5cEElJSeKbb74RQtR3g48aNUoMHDhQZGdnO5wqaLVahRD1Z1OtXr1anDhxQpw7d0689tprws/PT/z+97/36LYLUX9abHx8vPjyyy/F4cOHxZgxY8SYMWPs6xtOi50yZYrIzMwU27dvF927d++y02Lb0vbTp08Lg8EgHn30UXHq1Clx8uRJ8bOf/UwEBwfbu4+barsQQpw7d05IkiQ+/fTTRs/tCa97e9qenZ0tnn32WXH48GGRk5MjtmzZInr37i3GjRtnf25vfd295fPe3ve8N3zeG/zrX/8SPj4+jXq0hBDim2++EUlJSeLChQsOy7/44gv7YacfevPNN8WGDRvsPTN//vOfhSzLYu3atR3axqZ0Vrv3798vXnrpJZGZmSnOnz8v3n77bdG9e3cxb948+2PKy8tFjx49xNy5c8XJkyfFxo0bhZ+fH0+Ddzfp6eliypQpolu3biIwMFCMHj260XHpiRMniuDgYOHj4yNGjRrVaH3DqY67du0SQgixa9euZo/N5uTkCCGE+PTTT0VqaqoICAgQ/v7+YvDgwWLlypUO3c+drTPaLoQQNTU14rHHHhOhoaHCz89PzJw50z7vRIPc3Fwxbdo04evrK8LDw8VTTz3lcMpwZ2tL2z///HPxox/9SAQHB4vQ0FDx4x//2H5qrxBNt12I+ukD4uLimnwtPeV1d7bt+fn5Yty4caJbt27CYDCIxMRE8fTTTzfqfvfG192bPu/tec97y+ddCCHGjBkjfvrTnza5j4bXueE1bXDvvfc6zHt0vTfffFOkpKQIPz8/ERQUJEaOHOkwZUBn64x2Z2RkiFGjRtm/F1JSUsRf/vKXRodyjx07JsaOHSsMBoOIiYkRK1asaFcbJCG66FxJIiIiIjfBeYCIiIhIdRiAiIiISHUYgIiIiEh1GICIiIhIdRiAiIiISHUYgIiIiEh1GICIiIhIdRiAiIiISHUYgIiIiEh1GICIiIhIdRiAiIiISHUYgIiIiEh1/j/Pu8oNE0kY2gAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#RUN THIS ONLY IF WE FOUND POPULATED ISLANDS\n",
    "nSubGeoms = len(MAP.geoms)\n",
    "subGeoms = [MAP.geoms[n] for n in range(nSubGeoms)]\n",
    "subAreas = [subGeoms[n].area for n in range(nSubGeoms)]\n",
    "mainSubGeomNo = subAreas.index(np.max(subAreas))\n",
    "mainGeom = subGeoms[mainSubGeomNo]\n",
    "nonMainGeom = dummyPoly\n",
    "for geo in subGeoms:  #the \"nonMainGeom is all pieces of the state not in the biggest piece\n",
    "    if geo != mainGeom:\n",
    "        if nonMainGeom == dummyPoly:\n",
    "            nonMainGeom = geo\n",
    "        else:\n",
    "            nonMainGeom = nonMainGeom.union(geo)\n",
    "        \n",
    "print(\"Lets first identify which county each island belongs to.  Then we'll move the island to the closest county mainland\")\n",
    "hasIsland, isIsland = [False for c in range(nCounties)], [False for c in range(nCounties)]\n",
    "isIsland =  [False for t in range(nTracts)]\n",
    "islandXshift, islandYshift = [0. for t in range(nTracts)], [0. for t in range(nTracts)]\n",
    "islandList = list()\n",
    "for c in range(nCounties):\n",
    "    if countyGeom[c].intersects(nonMainGeom):  #this county contains an island.  Find all its island tracts\n",
    "        hasIsland[c] = True\n",
    "        if countyGeom[c].disjoint(mainGeom):  #need to connect the whole county\n",
    "            print(\"county\",c,\"is completely disconnected from mainland.  Move it to adjoin mainland\")\n",
    "            isIsland[c] = True\n",
    "            countyDist = [999999. for cc in range(nCounties)]  #default, to avoid picking island counties as closest to this one\n",
    "            for cc in range(nCounties):\n",
    "                if countyGeom[cc].intersects(mainGeom):\n",
    "                    countyDist[cc] = countyGeom[c].distance(countyGeom[cc].intersection(mainGeom) )\n",
    "            closestCounty = countyDist.index(np.min(countyDist))\n",
    "            p1, p2 = nearest_points(countyGeom[closestCounty],countyGeom[c])\n",
    "            for t in countyTractList[c]:\n",
    "                islandXshift[t], islandYshift[t]  = p1.x - p2.x , p1.y - p2.y\n",
    "            for t in countyTractList[c]:\n",
    "                plotPoly(tractGeom[t])\n",
    "                plotCenter(t,tractGeom[t])\n",
    "                plt.arrow(tractCP[t].x, tractCP[t].y,islandXshift[t], islandYshift[t])\n",
    "                tractGeom[t] = translate(tractGeom[t], xoff=islandXshift[t], yoff=islandYshift[t])                   \n",
    "                tractCP[t] = tractGeom[t].centroid\n",
    "                tractCPx[t], tractCPy[t] = tractCP[t].x, tractCP[t].y\n",
    "                plotPoly(tractGeom[t],0.2)\n",
    "        else: #move only the county's island tracts to connect with main geom\n",
    "            mainCountyGeom = countyGeom[c].intersection(mainGeom)\n",
    "            plotPoly(mainCountyGeom)\n",
    "            plotCenter(c,mainCountyGeom)\n",
    "            for t in countyTractList[c]:\n",
    "                if tractGeom[t].intersects(nonMainGeom) and t not in skipList:\n",
    "                    if tractGeom[t].intersects(mainCountyGeom):\n",
    "                        print(\"unit\",t,\"has island pieces.  We will reduce the tract to its main state component\")\n",
    "                        plotPoly(tractGeom[t],0.2)\n",
    "                        tractGeom[t] = tractGeom[t].intersection(mainCountyGeom)\n",
    "                        tractCP[t] = tractGeom[t].centroid\n",
    "                        tractCPx[t], tractCPy[t] = tractCP[t].x, tractCP[t].y\n",
    "                        plotPoly(tractGeom[t])\n",
    "                        plotCenter(t,tractGeom[t])\n",
    "                    else:    \n",
    "                        isIsland[t] = True\n",
    "                        print(\"unit\",t,\"is a true island.  We will move it to adjoin the mainland in same county.\")\n",
    "                        islandList.append(t)\n",
    "                        if tractGeom[t].geom_type != dummyPoly.geom_type :  #island tract is multiple geoms.  collapse to its largest isle\n",
    "                            isleGeos = [geo for geo in tractGeom[t].geoms]\n",
    "                            isleAreas = [geo.area for geo in isleGeos]\n",
    "                            biggestIsleNo = isleAreas.index(np.max(isleAreas))\n",
    "                            tractGeom[t] = isleGeos[biggestIsleNo]\n",
    "                            tractCP[t] = tractGeom[t].centroid\n",
    "                        p1, p2 = nearest_points(mainCountyGeom, tractGeom[t])\n",
    "                        islandXshift[t], islandYshift[t]  = p1.x - p2.x , p1.y - p2.y\n",
    "                        plotPoly(tractGeom[t])\n",
    "                        plotCenter(t,tractGeom[t])\n",
    "                        plt.arrow(tractCP[t].x, tractCP[t].y,islandXshift[t], islandYshift[t])\n",
    "                        tractGeom[t] = translate(tractGeom[t], xoff=islandXshift[t], yoff=islandYshift[t])                   \n",
    "                        tractCP[t] = tractGeom[t].centroid\n",
    "                        tractCPx[t], tractCPy[t] = tractCP[t].x, tractCP[t].y\n",
    "                        plotPoly(tractGeom[t],0.2)\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9a94118d-5863-4458-b77a-67d18cf01c2c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If you like my proposed translations, let's rebuild the MAP with the adjusted county geoms\n",
      "This would need adjustment for multi-county islands like Michigan UP\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#continuing with island triage - RUN ONLY WITH ISLANDS\n",
    "print(\"If you like my proposed translations, let's rebuild the MAP with the adjusted county geoms\")\n",
    "print(\"This would need adjustment for multi-county islands like Michigan UP\")\n",
    "for c in range(nCounties):\n",
    "    if hasIsland[c] :  #rebuild the county geom with the translated islands\n",
    "        countyGeom[c] = dummyPoly\n",
    "        for t in countyTractList[c]:\n",
    "            if t not in skipList:\n",
    "                if countyGeom[c] == dummyPoly:\n",
    "                    countyGeom[c] = tractGeom[t]\n",
    "                else:\n",
    "                    countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "MAP = countyGeom[0]\n",
    "plotPoly(countyGeom[0])\n",
    "for c in range(1,nCounties):\n",
    "    MAP = MAP.union(countyGeom[c])\n",
    "    plotPoly(countyGeom[c])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4aebe4ee-ee7b-4bf3-8413-f315556d453e",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "computing all county centerpoints, then plot them\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"computing all county centerpoints, then plot them\")\n",
    "countyCP  = list()\n",
    "cutCountyList = list()\n",
    "for c in range(nCounties):\n",
    "    cTL = countyTractList[c]\n",
    "    countyCP.append(getHDcp( [tractCP[v] for v in cTL], [tractPop[v] for v in cTL], [i for i in range(len(cTL) ) ] ) )\n",
    "    if countyCP[c].disjoint(countyGeom[c]):  #possible with weird-shaped county\n",
    "        countyCP[c] = nearest_points(countyGeom[c],countyCP[c])[0]\n",
    "    plotPoly(countyCP[c].buffer(0.03))\n",
    "    plotPoly(countyGeom[c],0.5)\n",
    "plotPoly(MAP)\n",
    "plt.show()   \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "207f3a55-e361-4777-ae46-41fe3d54a4b8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This code block reads in a csv with whole districts to be cut out of the map\n",
      "For NJ my input file says to cut out 0 districts out of 12\n",
      "There were no cut districts in NJ\n"
     ]
    }
   ],
   "source": [
    "print(\"This code block reads in a csv with whole districts to be cut out of the map\")\n",
    "unclippedMAP = MAP\n",
    "trimDF = pd.read_csv(\"state_map_files/cutNclipPolyLists.csv\")\n",
    "stateRows = trimDF[\"state\"].to_list()\n",
    "DFrow = stateRows.index(STATE)\n",
    "nClips = trimDF[\"nClipPoly\"][DFrow]\n",
    "nCuts  = trimDF[\"nCutPoly\"][DFrow]\n",
    "nCutDistricts = nCuts\n",
    "nStops = trimDF[\"nStopLines\"][DFrow]\n",
    "nDistricts = trimDF[\"nDistricts\"][DFrow]\n",
    "stopLines = list()  #the 'stoplines' stop wedge growth that hops across concave map areas (not currently used)\n",
    "cutCountyList = list()\n",
    "allCutLists, allCutPops = list(), list()\n",
    "print(\"For\",STATE,\"my input file says to cut out\",nCuts,\"districts out of\",nDistricts)\n",
    "if nCuts > 0:\n",
    "    cutList = list()\n",
    "    cutXs = ast.literal_eval(trimDF[\"cutXs\"][DFrow])\n",
    "    cutYs = ast.literal_eval(trimDF[\"cutYs\"][DFrow])\n",
    "    cutPoints = [Point(cutXs[i],cutYs[i]) for i in range(len(cutXs)) ]\n",
    "    for cutNo in range(nCuts):\n",
    "        print(\"performing cut no\",cutNo,\"for state\",STATE)  #first two cutPoints must form the cutLine\n",
    "        cutNotDone = True\n",
    "        thisCutPoints = [ cutPoints[int(4*cutNo)],cutPoints[int(4*cutNo+1)],cutPoints[int(4*cutNo+2)],cutPoints[int(4*cutNo+3)]  ]\n",
    "        while cutNotDone:\n",
    "            cutPoly = Polygon([thisCutPoints[0],thisCutPoints[1],thisCutPoints[2],thisCutPoints[3] ])\n",
    "            cutLine = LineString([thisCutPoints[0], thisCutPoints[1] ] )\n",
    "            cutList = list()\n",
    "            cutPop = 0.\n",
    "            for c in range(nCounties):\n",
    "                if cutPoly.intersects(countyGeom[c]):\n",
    "                    if cutPoly.contains(countyGeom[c]):\n",
    "                        cutList = cutList + countyTractList[c]\n",
    "                        cutPop += countyPop[c]\n",
    "                    else:\n",
    "                        for t in countyTractList[c]:\n",
    "                            if cutPoly.contains(tractCP[t]):\n",
    "                                cutList.append(t)\n",
    "                                cutPop += tractPop[t]\n",
    "                            if STATE == \"NC\":\n",
    "                                if t == 1828:\n",
    "                                    print(\"special for NC - include vtd 1828 from county 55 in the cut list for contiguity\")\n",
    "                                    cutList.append(t)\n",
    "                                    cutPop += tractPop[t]\n",
    "            print(\"the total proposed cutPop is\",cutPop,\". Compare to\",int(statePop/nDistricts) )\n",
    "\n",
    "            doIcut = input(\"enter 1 to apply the cut\")\n",
    "            if str(doIcut) == str(1):\n",
    "                cutNotDone = False\n",
    "                allCutLists.append(cutList)\n",
    "                allCutPops.append(cutPop)\n",
    "            else:\n",
    "                print(\"Here is the state and the last proposed cutPoly.\")\n",
    "                plotPoly(cutPoly)\n",
    "                plotPoly(MAP)\n",
    "                plt.show()\n",
    "                print(cutPoly)\n",
    "                oldPts = list(cutPoly.exterior.coords)\n",
    "                newPtXs = ast.literal_eval(input(\"enter alternate [ x0, x1 ] for the first two points\") )\n",
    "                newPtYs = ast.literal_eval(input(\"enter alternate [ y0, y1 ] for the first two points\") )\n",
    "                thisCutPoints = [Point(newPtXs[0],newPtYs[0]), Point(newPtXs[1],newPtYs[1]),oldPts[2], oldPts[3] ]\n",
    "allCutVTDs = list()\n",
    "for L in allCutLists:\n",
    "    for v in L:\n",
    "        allCutVTDs.append(v)\n",
    "if nCutDistricts == 0:\n",
    "    print(\"There were no cut districts in\",STATE)\n",
    "else:\n",
    "    print(\"here are your cut districts\")\n",
    "    plotPoly(MAP)\n",
    "    for i,L in enumerate(allCutLists):\n",
    "        cutGeo = tractGeom[L[0]]\n",
    "        for v in L:\n",
    "            cutGeo=cutGeo.union(tractGeom[v])\n",
    "        plotPoly(cutGeo,2)\n",
    "        plotCenter(i,cutGeo)\n",
    "        plotCenter(allCutPops[i],Point(cutGeo.centroid.x,cutGeo.centroid.y-0.5) )\n",
    "    plt.show()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "4c915415-6c44-4c43-9826-b565cebed95a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Write the vtd cutlists to a file\n"
     ]
    }
   ],
   "source": [
    "print(\"Write the vtd cutlists to a file\")\n",
    "cutDistrictNo = list()\n",
    "for v in allCutVTDs:\n",
    "    for i,L in enumerate(allCutLists):\n",
    "        if v in L:\n",
    "            cutDistrictNo.append(i)\n",
    "            break\n",
    "nbrDF = pd.DataFrame( {\"vtdNo\":allCutVTDs,\"cutDistrictNo\":cutDistrictNo} )\n",
    "outname = STATE+\"wholeDistrictCuts.csv\" \n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "nbrDF.to_csv(outpath)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "17721728-e5c0-4787-b430-9d7d94970667",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12 districts\n"
     ]
    }
   ],
   "source": [
    "countyPop = [0. for c in range(nCounties)]\n",
    "for t in range(nTracts):\n",
    "    countyPop[countyNo[t]] += tractPop[t]\n",
    "print(nDistricts,\"districts\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f3073320-8d92-45ba-beb2-fb8c08d7170d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Removed all whole districts.  Finalize stats before squishing in outcroppings.\n",
      "Of the total statePop 9288994.0 we ignore 0.0 as it is cut out of the map\n",
      "This excluded pop comes from a total of 5 tracts\n",
      "Our final adjusted number of state districts, excluded fixed cut-out is 12 rather than original 12\n",
      "Each district will be drawn to house 774082.833 = 1/ 12 of non-cutout state pop 9288994.0 vs original= 9288994.0\n",
      "Here is a county-level modified map with each county's fraction of a district pop\n",
      "working on county 0\n",
      "working on county 20\n",
      "here is the NJ map excluding cut and unpop coastal tracts\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Removed all whole districts.  Finalize stats before squishing in outcroppings.\")\n",
    "trueCountyPop = [countyPop[c] for c in range(nCounties)]\n",
    "trueCountyGeom = countyGeom.copy()\n",
    "countyPop = [0. for c in range(nCounties)]\n",
    "trueStatePop, true_nDistricts = np.sum(trueCountyPop), nDistricts\n",
    "trueCountyTractList = [list() for c in range(nCounties)]\n",
    "# minTractPop = 4.5  #already defined above\n",
    "populatedTractList = list()\n",
    "countyTractList = [list() for c in range(nCounties)]\n",
    "statePop, excludedPop = 0., 0.\n",
    "\n",
    "for t in range(nTracts):\n",
    "    trueCountyTractList[countyNo[t]].append(t)\n",
    "    if t in allCutVTDs or t in skipList:  #  or vtdPop[t] < minTractPop:  #need to keep low-pop vtds as VEST may have assigned votes to them\n",
    "        excludedPop += tractPop[t]\n",
    "    else:\n",
    "        populatedTractList.append(t)\n",
    "        countyTractList[countyNo[t]].append(t)\n",
    "        countyPop[countyNo[t]] += tractPop[t]\n",
    "        statePop += tractPop[t]\n",
    "        #tractPop[t] = max(tractPop[t],0.000001)  #avoid possible later div/zero errors for nil-vote vtds\n",
    "print(\"Of the total statePop\",statePop+excludedPop,\"we ignore\",excludedPop,\"as it is cut out of the map\") #,\n",
    "#\"or in sparsely populated areas (<\",minTractPop,\") per geom\")\n",
    "print(\"This excluded pop comes from a total of\",nTracts -len(populatedTractList),\"tracts\")\n",
    "true_nDistricts = nDistricts\n",
    "nDistricts -= nCutDistricts\n",
    "print(\"Our final adjusted number of state districts, excluded fixed cut-out is\",nDistricts,\"rather than original\",true_nDistricts)\n",
    "aDP = statePop/float(nDistricts)\n",
    "print(\"Each district will be drawn to house\",r3(aDP),\"= 1/\",nDistricts,\"of non-cutout state pop\",statePop,\"vs original=\",trueStatePop)\n",
    "print(\"Here is a county-level modified map with each county's fraction of a district pop\")\n",
    "\n",
    "vtdGeom = tractGeom.copy()\n",
    "nVTDs = len(vtdGeom)\n",
    "\n",
    "cutCountyList, uncutCountyList = list(), list()\n",
    "for c in range(nCounties):\n",
    "    if c%20 == 0:\n",
    "        print(\"working on county\",c)\n",
    "    if len(countyTractList[c]) == 0:  #no vtds added to county b/c all were in cut lists:\n",
    "        cutCountyList.append(c)\n",
    "    else:\n",
    "        uncutCountyList.append(c)\n",
    "        countyGeom[c] = tractGeom[countyTractList[c][0]]\n",
    "        for t in countyTractList[c]:\n",
    "            countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "uncutMAP = MAP\n",
    "MAP = countyGeom[uncutCountyList[0]]\n",
    "for c in uncutCountyList:\n",
    "    MAP = MAP.union(countyGeom[c])\n",
    "print(\"here is the\",STATE,\"map excluding cut and unpop coastal tracts\")\n",
    "\n",
    "for c in uncutCountyList:\n",
    "    plotPoly(countyGeom[c])\n",
    "    FONTSIZE = 11\n",
    "    if countyPop[c] / statePop < 0.02:\n",
    "        FONTSIZE = 7\n",
    "        plotCenter(r3(countyPop[c]/aDP),countyGeom[c], FONTSIZE)\n",
    "    else:\n",
    "        plotCenter(round(countyPop[c]/aDP,2),countyGeom[c], FONTSIZE)\n",
    "plotPoly(trueMAP,0.1)\n",
    "for c in cutCountyList:\n",
    "    plotPoly(countyGeom[c],0.2)\n",
    "    plotCenter(\"cut\",countyGeom[c],6)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "0062ac21-3328-4616-99ed-70c53e62b308",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now finalize the map topology before any squish operations.  Plot countyPop/aDP\n",
      "Working on county  0 distances\n",
      "Working on county  20 distances\n",
      "the max LAT-scaled distance between counties is 1.99668\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter user-picked max district diameter, or 0 to accept 1.99668  1.5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Working on county  0 neighbors\n",
      "Working on county  20 neighbors\n",
      "I have also identified each county's neighbors.  Let's visualize the counties with two or fewer neighbors\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiwAAAGdCAYAAAAxCSikAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/H5lhTAAAACXBIWXMAAA9hAAAPYQGoP6dpAABnkElEQVR4nO3deXxU5b0/8M+ZfZ9ksofshH3fDeIKgtS6oL1aq3W59t5fW/WqtNXSzdpqRWtb22rVqsVuVmttrVbLIogWAUEg7FvCFsi+zL6f8/z+iAQGAiQhyWyfd1952TmZOfOdw+TMZ57zLJIQQoCIiIgoganiXQARERHRuTCwEBERUcJjYCEiIqKEx8BCRERECY+BhYiIiBIeAwsRERElPAYWIiIiSngMLERERJTwNPEuoD8oioL6+npYrVZIkhTvcoiIiKgHhBDweDwoLCyESnX2NpSUCCz19fUoLi6OdxlERETUB3V1dSgqKjrrfVIisFitVgCdL9hms8W5GiIiIuoJt9uN4uLirs/xs0mJwHL8MpDNZmNgISIiSjI96c7BTrdERESU8BhYiIiIKOExsBAREVHCY2AhIiKihMfAQkRERAmPgYWIiIgSHgMLERERJTwGFiIiIkp4DCxERESU8BhYiIiIKOExsBAREVHCY2AhIiKihMfAQkRERAkvJVZrJqL05A5GcKTNj6giIIQAADjMOpQ4TD1a/ZWIkgcDCxElhFBUhjsQhSQBKkmChM/+qwIkAIGwjAZXEMpnwQQArAYtRuRboVWfaCxu94VRXefsuq3XqDEszxJzHyJKPgwsRBRXrkAEexs9MOnUsBu1XdsVISBE538VAZh0aowbYodKdfaWE4dZB4dZ13U7GJGxp8GDqKIAACRJwtAcM6wG7Zl2QUQJiIGFiOJGCIFd9W5UDc0asOcwaNUYV2Tvuq0oArUtXtQ0e7u2FdiNyLcbBqwGIjp/DCxENGiEEAhFFbT7wmh0B6EoAhOK7ed+YD9SqSQMy7PGbGtwBVBd5+zqB2PRazA0x3LO1hwiGjwMLEQ0YNYfaINOo+rqkwIAOo0KmSYdJpdkxrW2kxXYjSiwG7tuu4MRbDvm6gowGpUKw/IsMGjV8SqRKO0xsBDRgClxmNDsCWFicUa8S+kVm0EbU3NEVrC/yYtQVO7aVppljukrQ0QDi4GFiPpVXbsfrd4QBDpH+YzMt57zMYlOq1ZhdKGt67YQAofb/Djc5uvaxuHURAOLgYWIzluzO4ijzgCiskBZlgmTEuhyz0CQJAll2WaUwdy1rc0b6hpOLUkSDFoVKnMs0HA4NVG/YGAhoj5pdAVxzBkAAOTZ9JhUnJHWrQtZFj2yLPqu24GwjN0nDadWqyRU5lpg0vG0S9QX/Mshol6JyAo2He7AkAwjppSmdkvK+TDqYodTR2UFtS0+BCKd/WCEECh2mJB9UsghojNjYCGiHqtp9sIdjGBamQNqDvntFY1ahREn9ecRQuBoRyBmVt48mz5mtBIRncDAQkQ9sqveDbNenVDDkZOZJEkodphQ7DB1bWtyB7HlSEfX77MtOhRlms60C6K0wsBCROe045gLuVY9cm2cDXYg5dkMyDvpGDd7gjEtMA6TDsUOY1r3FaL0xcBCROcUlhUYdZw0bbDlWg3ItZ4IMK2fjUQ6HlgyjFqUZnEoNaUHBhYiOo2iCGyp6+icoVaSUJxp4mKBCSDboo/ppNvuC2PrUReAzj4xNqMWFdlmBhhKSQwsRHSaTw62Y0ppJnQaziGSyE5dmdrlj8QEGKtBg4psrolEqYGBhYi6CCGw8VAHSrNMDCtJyG7SYqIpo+v2qWsimfUaVHJRR0pSDCxE1MUdiCIQkWE38vJPKjh1TSRvKIrtx1xQPgswRp0aw3KtHKJOSYGBhYi62E1aXDwsG0t3NGJ6uSNm5lZKfha9BhNOCjC+UBQ7Tgoweo0aw/O4nAAlJgYWIuoihMDmIx0YX5zBsJIGzKcEmEBYxq4GN2SFAYYSDwMLEQEA/OEoNh92YkppJocwpymjTo3xRRldt4OR2ABj0WswlH1gKE4YWIgIzZ4g6tr9uLAyi0NiqYtBGxtgPKd04s0w6VDGeWBokDCwEKU5TzCCuvYAppQ64l0KJTjrKZ14233hmJl4OYyaBhIDC1Ea6/CFsafRgwsqGFao906dB8YdjMSMQlKrJFTmWmDS8aOGzh/fRURpyBWIYG+jBxkmLaqGZsW7HEoRNoM2phNvVFZQ2+KDPxzt2pZvN3BFauoTBhaiNLLjmAuhqAyrQYtpZZnse0ADSqNWYUS+NWZbgyvQtSI1AGjVKgzLs0CvYUdvOjsGFqI0IITAJwfbMabQxjWBKK4K7MaYFpZQVEZNsxfhqNK1Lceqx5AMrkpNsRhYiFJcbYsXrZ4Qxg6xw6LnnzwlFr1GjTGF9phtze4gth49MRpJo1KhMtfC4fZpjmcvohRV2+JFmzeM8mwzhuZY4l0OUY/l2gzItRm6bkdkBbUtXgTCMiRJghACDrMOJQ4OqU4nDCxEKUQIgb1NHjj9EQzPszKoUErQqlUYmW+L2dbuC8e0wqgkCUNzLWxFTGH8lyVKUkIIHGrzw+kPx2wflmfFyHz+aVNqO3VItawIHGjxwhuKdrXC2IxalGeZOS9MiuBZjSgJ+UJR/Gd/K2aUO1CebY53OURxp1ZJGJYXOyLJFYidF0aSJJRnmWE3seN5MmJgIUoCQggcaPXBFYgAAMw6DeaOzuM3R6KzsBtj54VRFIFDbT4caPV2bbMatKjIZitMMmBgIUowsiJQXefE8fPn8U6FZVkm9kkhOg8qlYSKU/6GTm2FUUkSKnLMHP6fgBhYiBKINxTF1jonZpQ7oFGr4l0OUco7tRXmeF+YmuYTrTCZJh1Kuchj3DGwECWIJncQR9r9uLAyG0DnOj+H2nwAgMpcC7/xEQ2C7vrCnDoiSa2SMCzXynlhBhkDC1GC2NfkgdWgRXWdE7IikGHqXBl3Z70bgbDMwEIUJ6eOSIrKCmo+mxfmuFybAUMyuEbSQJLE8ciYxNxuN+x2O1wuF2w227kfQJSg/OEomt0hdPjDOP6HWZFtRoZJd9bHEVF8NbmDaHAFu1ph9Bo1huVZoOWl3bPqzec3W1iI4qj9s8s+x6+Mm3Qa5Fr1vF5OlGTybAbknTQ7bzAiY2+jBxH5xBpJZVlmZJr55aOvGFiIBllNc+fkVrIiYDdqMbkkM94lEVE/M2jVGDvkxBpJQggcbvN39UsDwInteomBhWgQHWz1waBVoTI3I96lENEgkiQJZdlmlOHERI8uf+yQarVKQmWuBSYdP5q7w6NCNAiisoKtR52wGrQoz7ae+wFElPLsJi0mmDK6bnfXmTfPZkAhO/MCYGAhGnCNriAOtfkwtTSTc6sQ0RlpulnksdEVxJYjHV2307kzLwML0QA4eSp9IQRGFdgYVoio1/LtBuTbz96ZtzxNRhIysBD1k7p2P1q9oa7b5dlmTqVPRP2qu868h9r8ONga25m3ItucciMNz+sr3+LFiyFJEu6///6ubb/97W9x6aWXwmazQZIkOJ3OHu3r2WefRVlZGQwGA2bMmIENGzacT2lEA+54U+3xH71WhUklmV0/6fCNh4jiS5IklGebY8492WY9th51dZ2bth91xfSLSVZ9bmHZuHEjXnjhBYwfPz5mu9/vx5VXXokrr7wSixYt6tG+Xn/9dSxcuBDPP/88ZsyYgaeffhrz5s3D3r17kZub29cSifqFJxjB/mYvVJ99Wzk+MVSezYBJHJJMRAnGbtJi4kmdeSOygppmL4KRE6FlSIYRuSfNG5MM+jTTrdfrxeTJk/Gb3/wGjz76KCZOnIinn3465j6rV6/GZZddho6ODmRkZJx1fzNmzMC0adPwzDPPAAAURUFxcTHuvfdefPvb3z5nPZzplvqTLxTFwVYfooqArCiwGrQYlmtJueZVIkpfx5wBNLuDXbfNeg2G5ligHuQ5YQZ8ptu7774bV111FebMmYNHH320T0UeFw6HsWnTppjWGJVKhTlz5mDdunXdPiYUCiEUOtFXwO12n1cNlN5cgQgOtHihiM55EEw6NYbnWaHTsJMsEaWmIRnGmLWPvKEodta7oIjOVmSVJGForgUWfeJ0de11Ja+99ho2b96MjRs39ksBra2tkGUZeXl5Mdvz8vKwZ8+ebh/z+OOP45FHHumX56f0dKDFC2cgAgmdy8tPLM5gCwoRpS2LXoPxRRldt2VF4ECLF77P+r7UOwOYPzY/rufJXgWWuro63HfffVixYgUMhvhd+1q0aBEWLlzYddvtdqO4uDhu9VBy2VrnRLHDhAqO4CEi6pZaJWFY3olJLhUh4v6lrleBZdOmTWhubsbkyZO7tsmyjI8++gjPPPMMQqEQ1Gp1rwrIzs6GWq1GU1NTzPampibk5+d3+xi9Xg+9Xt+r5yECgA5fGIoQMUvFExHRmXlDUegSYB6pXlUwe/ZsbN++HdXV1V0/U6dOxS233ILq6upehxUA0Ol0mDJlClauXNm1TVEUrFy5ElVVVb3eH9HZ7G/2dn1rUBQBRel1n3MiorSy7agzZu6XeOlVC4vVasXYsWNjtpnNZmRlZXVtb2xsRGNjI2pqagAA27dvh9VqRUlJCRwOB4DO4LNgwQLcc889AICFCxfi9ttvx9SpUzF9+nQ8/fTT8Pl8uPPOO8/7BRKdbFpZJvY2eRCMKFBJnddlrxxbEO+yiIgS0o5jLowpiH9YAQZgptvnn38+pkPsxRdfDABYsmQJ7rjjDgBAbW0tWltbu+5z0003oaWlBT/4wQ/Q2NiIiRMnYunSpad1xCU6X5IkxazVoVWr4AlGYDVo41gVEVHi6fCFoZIk2E2JcX7s0zwsiYbzsFBfCSGw/kA7cqx6VOayEy4REdB5blxX24aZldkD+jy9+fyOfy8aojiSJAlVQ7OQadJibU1rzEyQRETpautRFyaWZMS7jBgMLEQAsix6VA3NwubDHXD6w/Euh4gobpz+MAxaFUy6xJk0DmBgIeoiSRJmVmbjmDOAPY2cPZmI0tOeRk9MX79EkVjxiSgBjCm0o8MXxuYjHQCAEocJ2RbO+0NEqW9fkwcVOeZ4l9EtBhaibmSadcj8bHK5w20+HGn3QwIwoSgDqkFeHIyIaDC0eEJQhECuNTFXceYlIaJzKM0yY3JJJsYU2rHxUHu8yyEi6ncRWUFNszchLwUdx8BC1EM6jQparuBMRClow8F2zCh3xLuMs+LZl6gXzDoNapq98S6DiKjfbDvqxNhCe8Jf7mYfFqJeGJFvRbsvjE2H2yFJEiYUZUCd4H/kRERnsrfRA7tRmzCz2Z4NAwtRLznMOjjMDkRkBZsOdyDTpI1Zhp2IKBlsPtKBQrsR+fbE7GR7Kl4SIuojrVqF6eUO5Fj12HCwHU3uYLxLIiI6J0UR+LimFUNzLEkTVgAGFqLzZjdqYTdqcbTDH+9SiIjOKhiRsaamFdPLHbAbE/8y0Ml4SYioj0JRGduPuj5bAdoKs56XhYgocbV5Q6ht8eGiYdmQpOTre8fAQnQGrkAEh1p96G4581yrHo3uIIoyTUnVpEpE6amu3Q9XIILpCT50+WwYWIi6cbjNB39Yxrghpw/1E0Kg2RNCWZYZjs9mwyUiSlSNriB84SjGDrHHu5Tzwj4sRN3IserhCUaxo94FWYltY5EkCXk2A8MKESU8VyCCelcgoWew7Sm2sBB1w6TTYHq5A+Gogq1HnTBq1RhVkPx/8ESUPkJRGTvrXZg5NDvepfQLBhais9BpVLDqNZBFdz1ZiIgSU127H03uIKoqsuJdSr9hYCHqhqII7Kx3IyzLKHGYkWPVx7skIqJzEkJg0+EO5FoNmFqWvB1su8PAQnSKUFTG+gPtuKDCAb1GHe9yiIh6pM0bwr4mLyaXZqTkuYuBhegU+5u8qMy1pOQfPBGlpl31bqhUQNXQ1LkEdCoGFkp7Qgi0eEJo9oTgC0UxMt+WFAuBEREFwjK21HVgdIENGabUHrnIwEJpKSIr2FrnhCRJUKsk5Fj1GJ5nhU7Dkf5ElBwOtfrQ7g+jqiIrKWeu7S0GFkoJNc0eeILR0/5oDVoVcix6ZJp0XRPA1bX70eAKYmpp5mmTwhERJTpFEdh4qB1FDhMml2TGu5xBw8BCSW9rnRNFmUZU5p6+lk8gLKPFE8LRDhcUISBJEnKt+qSenpqI0lezO4gDrT5MKc2EVp1eLcIMLJTU6tr9UKskZFm6H3Zs1KlRkmVCSZZpkCsjIupfW+ucMOvVuCCF5lbpDQYWSioufwQ1LV5IEiABGJJhTPr1MYiIzmVtTSvGFdlhNaTvgAAGFkoaQnRet509KjctOpgREQHAwVYfhuVZ0zqsAFz8kJKIJEkodpiw+UgHmj3BeJdDRDQo2rwhzrYNBhZKMiPyrZhS6oA/JOOTA21QFK7xQ0Spq9kdZFj5DAMLJaV8uwFhWUGUgYWIUtiRdj9Ks8zxLiMhMLBQ0gmEZXy0rwVVFVmc6I2IUpY3FIVZz66mx/FIUFLZWueEWiXhitF57HhLRCltb6M7rSaGOxcGFkoa2446UZhh5PVcIkoLKkniF7OTsD2dkkJNsxfZFj3DChGlhf1NHuTaDPEuI6EwsFBSaHYHUZhhjHcZREQDbvORDpj1GgzhOS8GAwslhcIMIzYcbIfTH453KUREA0JRBNbWtGJojoVf0LrBPiyUFMqyzSjNMuFgqw+H2vxd24UQMOk0GJF/+sKHRETJIhCW8enhdlxQkZV2ixr2FAMLJQ1JklCRY+m6rSgCW+o6YNar41gVEdH5afGEcKjNh1mV2exkexYMLJRUFEVg+zEXFNE5YdzYIXboNQwsRJScDrf54A1FMa3MEe9SEh4DCyWNw20+tHhCGFfEkEJEyW9nvQsWvQZjCrnifE8wsFBSCEcVbDvqwtUTCuNdChElqWBExqE2H4IRBVq1BJtBC5tBC4tBA7Wq55dihBBo9oTQ4OpchPXkR4rPfg/gnJd3ijONyLJwqoaeYmChpKDTqDCrMhtra1oxvjgDFk5XTUQ9dKjVhzZfGEatGuXZZhh1aoSjCjzBCDr8YRxp93ddZgY6Q8fJTg4gQghIkoQ8mx4TiuzsczKIeNanpJFp1mFmZTY+2teCi4axcxoRnd3RDj8aXEGUOkwoy46d4l6nUSHLomcLRxLh2ClKOpNKMrC3yRPvMogowdU7g5hW5uCMsSmCLSyUFJo9QRzrCADobJYtyuSkSkR0dr3pl0KJj4GFkoKiAIoQmFySyUtBRHROwYgM5pXUwktClBTy7QaMKbRj/YF2tHpD8S6HiBKcOxhBRBZQlFO70FKyYmChpGHQqlE1NAsHW33xLoWIElyu1YDSLBO21DnjXQr1EwYWSjqZJh1aPGxlIaIz21nvQrsvjCmlmee+MyUFBhZKKgdbfXAFIsi26OJdChElqEZXEDaDFqMKbPEuhfoRO91SUvGHozBq1b3qeOv0h3Gw1dftYzQqCdkWPbItOmi4QipRSjjmDLBlJQUxsFBSGVNohysQwabDHZAkQKdWoTjTBLtJG3O/Dl8YBz7r65Jp0mJicUa3gSUqK2j1hrG7wYOoogDonOUyy6xDaZZ5wF8PEfWvZncQGaecDyg1MLBQ0rEbtV3fniKygrp2Pw62+brW8xCn3OdsNGoV8u0G5NtjJ5Zqdgfx6aF26DVqjCm0QcXxkUQJp80bglolwWrQQq2S4ApEcKDVhwsqsuJdGg0ABhZKalq1ChU5ln7fb67NgFybAcGIjC11HRCis3XHqOMq0UTxIoRAbYsP7mAEQgDZFh0UAdS1ByALAZNOzbCSwhhYiM7CoFVjSqkDQgjsOOZGWJaRYdKhItvMCeyIBpErEMGOYy6MLbSjMrf/v6RQ4mNgIeoBSZIwrsgOAHD5I1h3oA0j821wmDlaiWgw7GvyYObQLH5RSGMcFkHUS3aTFjOHZnMCO6JBNKrAxkVP09x5BZbFixdDkiTcf//9XduCwSDuvvtuZGVlwWKx4IYbbkBTU9NZ93PHHXdAkqSYnyuvvPJ8SiMacPyiRzR4LHoNfKFovMugOOpzYNm4cSNeeOEFjB8/Pmb7Aw88gHfeeQdvvPEGPvzwQ9TX1+P6668/5/6uvPJKNDQ0dP385S9/6WtpRINCxcRCNCg6fGFsOtzBv7k016c+LF6vF7fccgtefPFFPProo13bXS4XXn75Zbz66qu4/PLLAQBLlizBqFGjsH79elxwwQVn3Kder0d+fn5fyiEiohR1oMWLUFThRHDUtxaWu+++G1dddRXmzJkTs33Tpk2IRCIx20eOHImSkhKsW7furPtcvXo1cnNzMWLECHzta19DW1vbGe8bCoXgdrtjfogGm6xwJViigeYMRDjFPgHoQwvLa6+9hs2bN2Pjxo2n/a6xsRE6nQ4ZGRkx2/Py8tDY2HjGfV555ZW4/vrrUV5ejtraWnznO9/B/PnzsW7dOqjVp8978fjjj+ORRx7pbelE/Wp8kR076l0YX5QR71KIUlYwLENWBNRxnrxRCAFfWEarJwRnIHLW+7Z6QpgzOm+QKksfvQosdXV1uO+++7BixQoYDIZzP6CHvvjFL3b9/3HjxmH8+PEYOnQoVq9ejdmzZ592/0WLFmHhwoVdt91uN4qLi/utHqKe0KpVEGxgIRpQMyqy8HFNKyaXZsKi79+ZOGRFoN0XRpsvhGBEOef9LXo1ssx6lDhMZ539etPh9vOuLRiRoVOrOMv2SXr1r79p0yY0Nzdj8uTJXdtkWcZHH32EZ555BsuWLUM4HIbT6YxpZWlqaupV/5SKigpkZ2ejpqam28Ci1+uh1+t7UzpRvxNCIMpLQkQDSq2ScGFlNg60eOELy13bhRDIsxlQYDfEzM0SCMto9YbQ4Q/jXH+eKgnINOlQ6jD32yzWuxvccJj7/vnU5A7iaIcfOrUaihBQTvpWVJRpQo41fT/7ehVYZs+eje3bt8dsu/POOzFy5Eg89NBDKC4uhlarxcqVK3HDDTcAAPbu3YsjR46gqqqqx89z9OhRtLW1oaCgoDflEQ2aDl8Yexo9mFyaEe9SiFKeWiVhWJ41ZpsQAs2eELYedUEI0RVaDFoVsi16FGbYB/0y0qbD7SjONCHX1vsrELUtXnT4wsizGTCl1HHa74UQONoRwJYjHQAARQiMKbTDoE2f5UJ6FVisVivGjh0bs81sNiMrK6tr+1133YWFCxfC4XDAZrPh3nvvRVVVVcwIoZEjR+Lxxx/HggUL4PV68cgjj+CGG25Afn4+amtr8eCDD6KyshLz5s3rh5dI1P+CURnFDiP0mvQ5WRAlEkmSkGczIK8P4WAg/Ht7Ay4antOry1aKIrCz3o1QVEZFjgVDz7IumiRJKHaYUOwwAegMMBsPdaAix4xsS3q0uvT71Py/+MUvoFKpcMMNNyAUCmHevHn4zW9+E3OfvXv3wuVyAQDUajW2bduG3//+93A6nSgsLMTcuXPx4x//mJd9KGHVNvtwYSUXWSOiTlPLHKhp9kJ8dglHkiTk2wzIs+ljLlkJIVDvCqLRFQCAPreSSJKE6eUO7Kx3wROMojzb3D8vJIFJQiR/t0G32w273Q6XywWbjcPfaOCt2d+KWcOy410GESUoIQQa3UE0uUOQAJz8QVtg79+Wobp2Pzr84aQcsdibz28ufkjUBxOK7dh+1NW1ICIR0ckkSUKB3YgCu3HAn6vYYYLVoMHa2lZcUJ6VsiOLuPghUR9YDVoEozJSoIGSiFJAhkmHaWUOrDtw5klXkx0DC1EfjS20Y8cxzrJMRIlBq1bBrNek7BcpBhaiPjLq1PCGoil7ciCi5JNn06PJHYp3GQOCfViIzsOkkgxsPNQBrVqCJEnItugwJMMYMyqAiGiw5NsM2HrUhXx7Ygz37k8MLETnwaBVY3p55yRPQgi0eEPYUucEABi1aozMt54WXoIRGY2uINzBCGSlc8Kr4xNfqSUJowqs0KjZ+ElEvZfKX5YYWIj6iSRJyLUakGvt/GbjC0VRXec87QSiVXeOHih2mE6biTMcVbCrwd0VZABgSIYxrafjJqKeUxQB1zkWZ0xWDCxEA8Ss12BSSWavHqPTqGLmUlAUgWPOANbsb8XEkox+X/yNiFJLWFZgM6TmeYLtzkQJTKXqnI571rBs7DjmStlvTkTUPwxaNVJ1GAADC1GSuKAiC/ubPHD6w/EuhYgSWKr2YmFgIUoix9cr6fAxtBBR92RFQFFSr52FgYUoyUwtc2BvkweBsBzvUogoATnMOnhC0XiX0e8YWIiS0IxyB6o/Gz5NRHQyo06NYCT1vtAwsBAlIUmSYNFrEI4q8S6FiBJMJCqgS8G5nFLvFRGliWF5Fmw50hHvMogowTR7grAbtfEuo98xsBAlKYNWjeF5Vmw42I69jR6uaUREADpbYFWq1BsrlJqzyxCliUyzDtPLHXAHI11LAtgMGgzNsaT0FN1EdGaBsIxwVIFOk1ptEgwsRCnAZtBi8mez6roCneFFCCDDpMXQHEucqyOiwdTmC6VcWAEYWIhSjt14Irx0+MLYdLgDKunEomhCCBQ7TMi2cH0iolRUmmWOdwkDgoGFKIVlmnWYYtbFbBNCoK49gE1tHQAEKnOssJtSr4MeUbqSU3DSOICBhSjtSJKEkiwTSrJMAICaZg9qWjyw6LUYnse+L0TJ7tRV4FMFAwtRmqvMtQIA3MEINhxsR7ZVz34vREnK6Q/DolfHu4wBkXq9coioT2wGLWZUZMGi12DDwXYOkyZKQvubvV1fQlINAwsRxcizGTC+yI41Na0puYAaUapq84aQkYITxh3HwEJEpzFo1ZhRnoWPa1vZ0kKUJPY1eTEsLzVbVwAGFiI6A51GhRnlWfjP/lZEZK5ZRJSohBBYV9uG0QW2eJcyoBhYiOiMdBoVZlVm45MD7Sm5+itRKth8xIkJxfaUn56AgYWIzkqlknBhZRZ21ruw/aiL/VqIEogvFIVeo4JJl/qDflP/FRLReZMkCVNKHQhGZGw96uzarpIklOeYYTOk9jc7okS1q8GNqaWZ8S5jUDCwEFGPGbRqTCo5cXKUFYGDrV7UNnu7tuk1alTmWlJyLROiROIKRGA1aNJmskcGFiLqM7VKOm3Oh2BExr4mD6KKgCIE1JKEkQVW6DWpOZkVUbzUNHsxJU1aVwAGFiLqZwatGmOH2LtuR2QFexs9CH820qg404QcKxdeJDofgbAMJc2mHGBgIaIBpVWrYgLMkTY/Nh1uR7ZFn7KryhINJCEEPj3cjlmV2fEuZVDxIjMRDaqSLBOmlDoAANV1zvgWQ5RkghEZH+5rwbQyR9r0XTmOgYWI4qI0y4yhOWas4cR0RD1WXefEJcNzYNCmX58wBhYiihurQYuZQ7Ow4WB7vEshSgpt3nDatawcx8BCRHGlUkkYV2TH+gNt2HHMhUCYM+oSdUdWBHJt6dthnZ1uiSjubAYtLqjIQjiq4ECrF/7PQovNoEVlriXO1RElhk8OtGF6uSPeZcQNAwsRJQydRoWR+ScWcGv1hvDJgTaU55iRazXEsTKi+Np0uANji+zQqNP3wkj6vnIiSnjZFj1mVGTBG4xiw0EuwEjpqd4ZQK5Vn/ZLYDCwEFHCq8ixYFpZJnbWu+NdCtGga3AFUOwwxbuMuGNgIaKkcLQjAIueV7EpvYSjCjQqflQD7MNCRAnMHYxgf5MXgECB3YgR+dZzPoYoleyod2FCUUa8y0gIDCxEFDdRWcH+Zi9CUQVCiK75JYQQUARg0WswuSQjbeedIBJCQK3i+x9gYCGi83C4zYd2X+xEVlq1hEK7ERkmbbdBo90XxqE2HwBAo5IwLNcKoy79Zu0kOpdDrT6UOLje1nEMLETUa4oisP5gGypzLJhUEru8fSgqo9EVxOF2PyQAJ68nqwiBTJMOk095DBHFanIH0e4PoyybgeU4BhYi6rVPDrZjaqkDOs3pnQH1GjVKs8wozYpDYUQpQkLnF4ODrT6UM7QAYGAhol7a0+hGWbap27BCRP0j12ZArs2AFk8Inx5qh92oxbC89O50zsBCRGflD0dR0+yFrHR2hC12GDnrLNEAcfrD2FXvhumzIfwSAI1ahWPOANbUtOLz4wuRY03P9YQYWIioW0c7/Gh0BWExaDC6wJbWU4ITDZY9jR7MrMzu9neXjhjkYhIMAwsRAQBcgQiOdQQQispQBGA3ajG1LH0XWiMabHsbPRie5pd9zoaBhSiNyIrAsY4A2nyh04YcWw0aVOSYYdByiDFRPHhDEU6OeBYMLERJTgiBuvbTQ8jJQ4qPT8qmkoCiTBNKsrguCVEiqW3xoiLbEu8yEhoDC1GSkRWB/c0eBMInVi4udphQksW5TYiSldMfxtAcBpazYWAhSnCKIlDT4oUvFAUAqFUSKnMtMOn450uUCtp9YdiNuniXkfB4xiNKQIoisKvBjVBUgVolYViuBWauVEyUkmpbvJjGDu7nxDMgUQI52uFHkzsESQJGF9jYAZYoxbmDEVgN/CjuCR4lojjzhqLY2+gBAAzJMGJKKfuiEKWLfY0eTh/QQ+c1E9TixYshSRLuv//+rm3BYBB33303srKyYLFYcMMNN6Cpqems+xFC4Ac/+AEKCgpgNBoxZ84c7N+//3xKI0powYiMLUc6sPlIB+qdAUwuycCU0kzk2zmDLFG6CEcVaDkhY4/1+Uht3LgRL7zwAsaPHx+z/YEHHsA777yDN954Ax9++CHq6+tx/fXXn3VfTz75JH71q1/h+eefxyeffAKz2Yx58+YhGAz2tTyihBCMyKhp9qK6zonqOmdXSKlt8WJCUQYml2RieJ71tDlRiCj1bT/mxNgh9niXkTT6dEnI6/XilltuwYsvvohHH320a7vL5cLLL7+MV199FZdffjkAYMmSJRg1ahTWr1+PCy644LR9CSHw9NNP43vf+x6uvfZaAMAf/vAH5OXl4a233sIXv/jFvpRIFBf1zgAa3UEcjx96jRpFDiMqDRyuSEQnhKIy1CoV1Cp+WempPrWw3H333bjqqqswZ86cmO2bNm1CJBKJ2T5y5EiUlJRg3bp13e7r4MGDaGxsjHmM3W7HjBkzzviYUCgEt9sd80MUTzXNXmw63A4AmFySiUmf/YwutMFm0Ma5OiJKNNuPujCerSu90usWltdeew2bN2/Gxo0bT/tdY2MjdDodMjIyYrbn5eWhsbGx2/0d356Xl9fjxzz++ON45JFHels60YCornOiwG5AZS5bUYjo3EJRGVq1Ciq2rvRKr1pY6urqcN999+HPf/4zDIb4dQ5ctGgRXC5X109dXV3caqH0JYTA5iMdyLbokGdjZ1ki6pkdx9wYx9aVXutVYNm0aROam5sxefJkaDQaaDQafPjhh/jVr34FjUaDvLw8hMNhOJ3OmMc1NTUhPz+/230e337qSKKzPUav18Nms8X8EA0WVyCCTYfbselwB0bmW1GUyXV5iKhnhBAQQrB1pQ96dUlo9uzZ2L59e8y2O++8EyNHjsRDDz2E4uJiaLVarFy5EjfccAMAYO/evThy5Aiqqqq63Wd5eTny8/OxcuVKTJw4EQDgdrvxySef4Gtf+1ofXhLR+YnICpo9IbR6Ql2LB57MatBgckkmR/YQUa/trHdjTCFbV/qiV4HFarVi7NixMdvMZjOysrK6tt91111YuHAhHA4HbDYb7r33XlRVVcWMEBo5ciQef/xxLFiwoGsel0cffRTDhg1DeXk5vv/976OwsBDXXXfd+b9CorMQQuBAqw/uQKRrm1atQq5Nj3FD7PwWRET9KhRVYNRxBuu+6PeZbn/xi19ApVLhhhtuQCgUwrx58/Cb3/wm5j579+6Fy+Xquv3ggw/C5/Phf//3f+F0OjFr1iwsXbo0rv1kKHWFowp2NbihCAEJQHm2maukEtGAi8oKtGp+CeorSQjRXat3UnG73bDb7XC5XOzPQmfV6g3hQIsPU0ozOf8BEQ2qvY0eFGUauZDpSXrz+c2jRmnlcJsf08u5bgcRDT5fOMqwch64iAGlFbaqEFE8KIrAwRZfvMtIagwsREREA2xHvQtXjS+IdxlJjYGF0ordqEVduz/eZRBRGhFCIBxVYNBydND5YGChtFKebYY7GEGTmyuBE9Hg2N3gwagCDgg5XwwslHbGFNpxtCMQ7zKIKE342dm2XzCwUNrxBCOIykq8yyCiNBCOKtBreCmoPzDyUVpp8YRwuM2HGRVZ8S6FiNLAviYPhudzYsr+wMBCacEdjGBvowc2gxZTyzgPCxENjrDMFpb+wsBCSUUIgdoWL7whGQBwfFYVcdL/j7n/Z/816dSYxqBCRJS0GFgo4SmKwN4mDwIRGUIAw/IsqDRo410WEdFZBSMydGp2Fe0vDCyUkHyhKPY1eSAAqCQJw/MsMOn4diWi5LGvyYMxhfZ4l5Ey+AlAcScrAofbfHAFIgA6L+OYdGpMKMqAilPpE1GSUgSXA+lPDCx0TooiEIzKCEYURBUFOrUK2q4fCZIU+wcphEBUEYjKAmFZQbsvDFcgEtPH5OQlwlUSUOowoyKHPemJKHUIIc59J+oxBhYC0PmHdaDVB/dnrRzHQ4iEzksyeq0Keo0KapUEf0hGRFYQiiqQle7/INUqCTqNChqVhCyzHmVZptOCDRFRqmr2BOEw6+JdRkphYEljwYiM3Q3urhE2FdkWDGUrBxHReTvWEcCkksx4l5FSGFjSjKII7G50IxRVoNeo2E+EiGgA8GJQ/2NgSQOyIrDns5AiARhVYOOqoUREA4hfA/sfA0uKkhWB3Q1uhGUFKknCyHwrQwoR0SBgZ9uBwcCSQtq8IRxp90MAUEsSRhZYOSU0EdEgq23xcdTjAGBgSQGvbTiCXKMOGSFgzJgs6I2cBZaIKF48wQgqcxlY+hsDSxLyu8NoPuxCzUf7ENhxAONNGbBpMwAAaz7ahdkLL49vgUREaYwXhAYGA0sScDb7sePtanj310Hvj2CYuRQaACMBwF6GqBJBU7ARx8IhlF0xC0IRkDjyh4ho0IWiMjQ8/w4IBpYEJYRA9dL9aFy1BdlhQBFRSHYjQjm5aDzaCAlAQzgEfbYZKrUKHk8IU+2lcL+3Dat3HcLMr8yC3sh/XiKiwbSz3o0JRRnxLiMl8RMtwQgh4GoOYPd/DqL403Y0+sMw/dcsTJpZAo3uzB1ow4Eoti6vRdOyw5h4LBP7vvsvlH3vSlgdhkGsnogofQkhICuC6wcNEAaWBNJ40Iktzy5FdkQChIKtNiOu+NnN0BnO/c+k1qkQWrUJJQYz6vxHsS+kg2pnG4ZNy+vR44mI6PxU1zkxusAW7zJSFj/JEsjmZ5fBEIwi847ZKB6T0+tLOv4MM0S7F+XmEhSbALx7AH/788f40vM3DkzBRETURSVJ+PMnh3HdpCHItbJ1u79JIgVmuHG73bDb7XC5XLDZkjPdbl++D5H3tkKaPRqTrh7T5/1EwzI2vbMH4sPtKDINAQCsCXcgr9SC4VdOwJARWf1VMhERAQhHFWw50oF8uwGlWeZ4l5NUevP5zcCSAHas3A//25vhLHLgim/O6ZdVjV0tAWx9Zwc6Nu5FgU4Lg1oHhy4bkZuGo3xSXj9UTUSU3gJhGTvqXdBrVBhdYINGrYp3SUmHgSWJ/Ovhf6HYHUZjrgmzv3kFNAMwfX44EMXbT63DBT5gs/swrvnNrf3+HERE6aTeGUC9M4AppZn98iUzXfXm85txMI7CgSgyO9w4KMmY++15AxJWAEBn1CA7v/N6akCo4W4LDMjzEBGlg5pmD/zhKKaWORhWBhEDSxxEwzJC/giO7etAji4Tw6+fOeBv+ik3jMMR/1GMNOjRvPg/+Mc9f0FLnQeKrAzo8xIRpZK9jR5o1SpU5lrjXUra4SihQRQJy1jx05WwNbVCAxV8IopMtQHFpQN/GcvqMKDql1+Epz2Id777L1xgzULL06uxLeSEZvgQGPMyMezSYcjM4/oXRETd2dfkgUmnRrHDFO9S0hL7sAwSWVbwz4fewlR1FvYWqZFTmQvPoUYUTK1A5bSiQa/H2eTHx3/cBP2xOkgA9DKgkVTwmNVQ2y0YctFYDK8qYnMnERGA2hYv1JKEsmyOAupP7HSbIFqOurHjbxsRamiDIRCBSdLA8aWZqJxRHO/SThMORPHp65vgrz0G4Q1iiMqKgBxEYGwRKi8fifyKzHiXSEQUF7UtXgDA0By2QPe33nx+85LQAAl4wqh7ahmUSBCSwwztiGKUXDYK+eUZ8S6tWzqjBjPvmNF1+8Mlm+HZuBNlu5pwdMdRbDerIIdl+NVGFE0tBYRAdmU+HEOssOcY2RJDRClHCIHNR5zItxswJMMY73LSHgPLAFEUAY2kgf6S6Zh944h4l9Nrl9w5GbhzMj79WzVcH+4AYETQG8Z0ewEOfrgdkCS0rdmDNgABEUUow4SSK6chb6gD4WAUnvYg1GoV3E0uBDs8yCjNhT3XAnuOEQaLNt4vj4jorPzhKDYfdmJyaQZMOn5UJgJeEhogn75bC93725B332zklSVGTf0hHIhCa1BDCMDnDKH1kAuNO+vg3VqDjIiE428mrUqDiBJFVCiQoUAnqSF99r9jFhOu+fFVUHGBMCJKQHsbO4ctTyzOYOvxAOMloThrPeqBb9l6NJn0GFeaWkPfdJ+tbyRJnSOPrA4DyifnAV+eCmeTH15nCHqjBmqNCnqTBgarFmq1CkFfBJ62ID56ZRNm+NXY9N5BTPt8xVmfSwgBOarA2x5CwBuBHFVQMNQOtYaj8Ymo//lCUWw96sTwPCtGWFLr3J0K2MLSj5qPuLHlldXIbAugTaXg0h/fAKNFF7d6EpHPFcLa7/4VGWod/IgiqpagGHWQtGqIiAIpGgU0GkiBEHRRQCupoELnNxwVJPhEBEp5HkZcMwUFFfz2Q0T943CbD+2+MCaVcIDBYOIooUEW8kew7KE3MFKfgcORDjgun4gJ80dCoxuYmWuTXTgYxf71dXAfbkaow41IqxuQFUgaNaDTAMEIVDYTrEMLYc7NhC3PCqNFCzmqYM97WyHvOQKbpEOHFIF5UiVGzx8Hew47xBFR7wUjMrYccaLYYURRJudXGWwMLIOgfn87jm4+DOfuw9C1eWFXG3DAYMB1j30Oai6ANaAURaBuZytq/rUR+gYndJIaLj2Qc8kEjLx0KAxmduolonNjX5X441pCAyQSltFQ48TSH76NhmdXIvjxLghPEKpRxRj6vatww+LPxzWsfPTRR7j66qtRWFgISZLw1ltvnXaf3bt345prroHdbofZbMa0adNw5MiRM+7zxRdfxEUXXYTMzExkZmZizpw52LBhwwC+inNTqSSUjsvB7EWfw4ynboLlhukQWi2Cy6uxedHfsOLht7B/wzHIES47QESn8wQjWFvbihyrHpNKuHhhsmCn2x5QFIGPf7ce0raD0EtqaEUU+msvwOTLKiAl0EgXn8+HCRMm4L//+79x/fXXn/b72tpazJo1C3fddRceeeQR2Gw27Ny5EwaD4Yz7XL16NW6++WbMnDkTBoMBTzzxBObOnYudO3diyJAhA/lyekSrU2P0xeUYfXE5/O4wdr+/F761O+H888f4+E8RREpyMOKaqRgyjCclIupcuNAXkjFzaHa8S6Fe4iWhHqh+bw+U5TvgG1eEkVeMgaPQnPAjVSRJwj/+8Q9cd911Xdu++MUvQqvV4o9//GOf9yvLMjIzM/HMM8/gtttu64dKB0Z7gw87/1WNyI5DsEs6OBGGYfxQjLlqPDLyeJ2aKN1EZQUbD3WgIseMPNuZv6TR4OKw5n7mOdKCqBzCxbdPT/igciaKouDdd9/Fgw8+iHnz5mHLli0oLy/HokWLYkLNufj9fkQiETgcjoErth84Csy46H8uhFBm4tjeNjjf+RRKdS32bz0Mp07AMWscRl8+DEYrR3ERpboGVwBH2vyYXu6AOoFaxal3kvPTd5ANmzsONrUO1f/aFe9S+qy5uRlerxeLFy/GlVdeieXLl2PBggW4/vrr8eGHH/Z4Pw899BAKCwsxZ86cAay2/0gqCUWjsjH7wStR9bMvwnbTTAijHuGV27D1e3/Hiu//HXs+PoJoWI53qUQ0ALbWOREIy5hRkcWwkuTYwtIDeeV27JRDCK/YgtqSHJRPzE26WVoVpbMD6rXXXosHHngAADBx4kSsXbsWzz//PC655JJz7mPx4sV47bXXsHr16rP2e0lUGq0aI2YWY8TMYgS8Yez+oAb4aBs8f12Hda9HESnOxvBrpmHIcPZ3IUp23lAU2+qcGF+cAYueH3WpgP+KPSBJEkbffxX2PP0uXH/4CB++EoI0vAhFM0agZFwOdIbEP4zZ2dnQaDQYPXp0zPZRo0ZhzZo153z8U089hcWLF+P999/H+PHjB6rMQWO06DD56tHA1aPhbPJj57+2AtsPoOm5ldiLMAwTKjH28+Ngz2F/F6Jks6/Jg1BEwcxKdqxNJYn/SZsgCoZmIvfnX0LTITdc726Gsu8YnPubcUxEEMqzY9LtFyOnKHHXDNLpdJg2bRr27t0bs33fvn0oLS0962OffPJJPPbYY1i2bBmmTp06kGXGRUaeCRfeVQWhXNDZ3+XtjRBbarGv+hA69EDe5ZMw8uJy6E2c34UokQUjMjYf6cCIPCuyLPp4l0P9jIGlF9RaFQqHZaDw/ssBAM4mP7b9YxPUu47g8FPLsFsJI6QCkO/AqAUzUDRicDumer1e1NTUdN0+ePAgqqur4XA4UFJSgm9961u46aabcPHFF+Oyyy7D0qVL8c4772D16tVdj7ntttswZMgQPP744wCAJ554Aj/4wQ/w6quvoqysDI2NjQAAi8UCi8UyqK9voB3v71I0aj4iYRn71x9Bx7JNCP57Mza9twn+bDMqrp6O0vG5nByQKME0u4M42OpDVUUWL+mmKA5r7gfRiIzaTxvgPNyMQEMbooeakSXpYfrCNIyYdfbWi/60evVqXHbZZadtv/322/HKK68AAH73u9/h8ccfx9GjRzFixAg88sgjuPbaa7vue+mll6KsrKzr/mVlZTh8+PBp+3z44Yfxwx/+cCBeRsLxOUPYuWw33J/sRoaigVeEgcohGHPdFGQXWXhyJIqzbUedMOnUqMzlgoXJhlPzx5lQBFY+8Co0Ffm49L7Z8S6H+okQAs2H3djzzhaImmOwSjq0aWRc+uMvdK1iTUSDxx+OYssRJ8YV2WEz8JJtMuI8LHEkFIFVv/4ADkkHpYgdvs5Gjio4sqMFthwzHIXmhG+pkCQJeWV25N17KVwtAVT/6O+QFCTUbMdE6eJQqw8d/jBmDuUloHTBwNJPhCKw/5M6HHjjY2TLakhzxmHq1aPiXVZCCnjDqH5rG4Ib98Iu6dAmBKqlCDTDi1E5ZywKKzMTOgS0HHFhw1PvIkelwbQfL4BWz1W5iQZLMCJja50TQzKNmFSSGe9yaBAxsJwnoQjs/ugg6t5aj2xoIQwa5N92KYpG58S7tITTXu/Dllc/hvFIGwBAlOai5KYqeNv8cC/fArG3Do37mrBfhKEUZaPiikkoHpMNtTZxOrh+8tZe2P6zDzoNUHDXZTDZOFMu0WBo9YZwqNUHg1aN6eUOtqqkIQaW87Tm5bXI3euCLyph7P/NxpThiT1l/WATQuDwtmbs/+saZHplqBCBNGMEJl47HkZL54d9dpEFZRPmQVEEGmqd8K7YDrGvDq1LVqNORBHKtqBo9iRUTCmI+5w3+1buxWXmTEhDMlA8JjeutRClAyEENh9xwm7UYGoZz6/pjIHlPBVNKsPBrR+gQmtC/bY6DGFgAQBEwzJ2rqxB84pNcChaQCPDeN10TLqo7IzrMalUEoYMy8SQYRdDCIH2eh/2vr8TYtsBuP+6Fp++rsBn1SP3orEYNrMsLq0bNz35OTQ/sg7OXXWD/txE6abdF8aOYy5ML3fAoOWl13TXq7b25557DuPHj4fNZoPNZkNVVRX+/e9/d/2+trYWCxYsQE5ODmw2G2688UY0NTWddZ8//OEPIUlSzM/IkSP79mrioHzqEFz2q1vQLPvhOdQY73LiztsRwpqX1uLjb76G0NJqwGZC3v+7DHN+ehPGXFbR48UjJUlC1hALZt4+A1f87GaM/P410F86FkKOIvDeZmz7/t+x/NtvoPrdPfC7wwP7ok5SX+MEAHhF8i1NQJQsDrf5sPFQOzr8YVw8PIdhhQD0soWlqKgIixcvxrBhwyCEwO9//3tce+212LJlC8rKyjB37lxMmDABq1atAgB8//vfx9VXX43169dDpTrzB9WYMWPw/vvvnyhKk1wNP+FgFNkqPdz29GxdEYrAkR0t2PfmWlidQUAoEMMKMeKLF8CeY+yX57BlGzHl+nHA9eMQ8ISx/+ND8Hy0FYHl1di2vBpuoxq5F43DiIsrBmwFZiEE6l9cgRJTEYbNHjsgz0GUzkJRGZsPO1GSZcI0Xv6hU5z3PCwOhwM//elPUVxcjPnz56Ojo6NrLLXL5UJmZiaWL19+xtV9f/jDH+Ktt95CdXV1n2uI9zwsG97YCsPaA8i860IUj02ffg1BbwTb3tsFz9odyIAO7eoosi+biDGzhw3avCQBbxj71xxC00dbYfV1rrjsMWtQMHsShs0shb4f6/j7j1djuk+NDzqa8OUXvtBv+yVKd0II7G3ywBeSMbkkgx1q08igzMMiyzLeeOMN+Hw+VFVVoba2FpIkQa8/sX6DwWCASqXCmjVrzhhYAGD//v0oLCyEwWBAVVUVHn/8cZSUlJzx/qFQCKFQqOu22+3u68voF76jLXBHfBhRkR5D7JoOu7Dj9fUwHm2HJAFKrh35X6jC5OGD33PfaNFh/JXDgSuHI+ANY++HB+D+zzb43t6ITf/cAF+mESXzpmLo1AJodOfXrKxuOArYSnHtY1f1U/VEqUkIgb9sqENEVlCWbYZRq4ZWLXWdHyQAp35Trsgxc/I3OqteB5bt27ejqqoKwWAQFosF//jHPzB69Gjk5OTAbDbjoYcewk9+8hMIIfDtb38bsiyjoaHhjPubMWMGXnnlFYwYMQINDQ145JFHcNFFF2HHjh2wWrufZvnxxx/HI4880tvS++zo7mbs+NN/gKgMKAokWUASnT8aRUAPNUospfjk1U24+CsXDFpdg8nTHsSeVfvg/GQXMsMqSIhAdcFITLh63IBdgukto0WHiVeNBK4aCW9HELtX7gXW74b79Y+x/jUZwTwbKj43tc9rAZXpTXCG26EPRAD0z6UuolQkSRK+NKMEQggcavOjzRuC3ahFRU5qrT9Gg6vXl4TC4TCOHDkCl8uFv/3tb3jppZfw4YcfYvTo0Vi+fDm+9rWv4eDBg1CpVLj55puxa9cuTJ8+Hc8991yP9u90OlFaWoqf//znuOuuu7q9T3ctLMXFxQNySSjoi2Dtor9CVklQbEZIGjVUOjXUGg1UOi20NhNMuZkw59hROi477sNuz0fTIRe2/eo96KMKQno1IAAJAqqoAovQICoUeDMMKL5iEkbMLIEqSRYAdDb5sXvZDvi21CBD0cAnIpCLszH8qikoHJkFVQ8nqdu9pg7Wfx2CK9yBMT+/ZoCrJkotde1+tHhDmMzJ3ugkA3pJSKfTobKyEgAwZcoUbNy4Eb/85S/xwgsvYO7cuaitrUVrays0Gg0yMjKQn5+PioqKHu8/IyMDw4cPj1l1+FR6vT7m0tNAWv+7NdBBwsSHr4clM3VHhuxffwR1f/oIOkjQTq9E+HATVFoNIEnQWI2wjivD0KlFSblmTkaeCVW3TYf48jS0HfNh97vVkHcfRtNvP8B+EYZq2BAMnz8R+RX2s17SqpxeiB1/24AcQy7CwWhSh1OiwVbsMCHTrMOa/a2YVp4JvYYjf6h3zvuMqyhKTGsHAGRnd66hs2rVKjQ3N+Oaa3r+bdTr9aK2thZf/vKXz7e0fqHRaxGBgDljcALSYAv6Iji0rRW+1z9BKMOMC++/Erbs1LzcIUkSsossuOj/zYIQF6Kh1gnPu1sg9h9DfU0LdiEC/dgyjPrceGQVxjZdCyHwj/v+ipn2IqzVKbiRYYWo1yx6DS6szMLGQx3QqCVIAIbnWWHW8++Jzq1X75JFixZh/vz5KCkpgcfjwauvvorVq1dj2bJlAIAlS5Zg1KhRyMnJwbp163DffffhgQcewIgRI7r2MXv2bCxYsAD33HMPAOCb3/wmrr76apSWlqK+vh4PP/ww1Go1br755n58mX03ZMYwtO48BndrsN+G6CYCb0cIKx57F7nhILSSGl4lgsu+fR0MlvTo9CZJEgorM1F43+VQZAVHd7fB9d4mKNsO4uD2o9iikWGZMhyj546GLduINxevw0x7EVY7G3Dr8zfGu3yipCVJEqaXOyCEwH/2t3KOFeqxXgWW5uZm3HbbbWhoaIDdbsf48eOxbNkyXHHFFQCAvXv3YtGiRWhvb0dZWRm++93v4oEHHojZx/FLRscdPXoUN998M9ra2pCTk4NZs2Zh/fr1yMlJjLV4CiodaIbA0V2NsF9SHu9yuiVHFez56CDqV1VD5w5CVgGyTgPJaoQu0wpdhgU6mwWFYwuhM2hQv7sRx/6+FpPNRdier2DyjVOQVWiG3pQeYeVUKrUKJWNzUDL2SsgRBYe2NsL5702Irt+LPZ/UwKUDMgJhwFKGy78xN97lEiU9IQQ+rmnD9HIH1Am80CkllvOehyURDPQ8LMvufxVGWcBw4SiMv3ocDObE+WBvPOjE7p/9C1aNHu0GAcuoUsj+EEKtTghPAOqIDLUsoIEEnaSGACAg4DJrMO6u2SgYyg5wZxIJyajZUIejyzcjyyNjb1DGF371X9Ce5/BoonTmD0ex+bATU8sy2bpCvfr8ZmDpgbZ6Dzb/YQ0s9U7IEAhX5GHyzVXIyDP1+3P11qGtjXC+8jHUkhojfvL5M3YElaMK2o55IUcUWLOMsGSmZp8cIkpctS1euAIRTCrm5HDUiYFlgPjdYWx5cwsiW2pgkjRot+kw5osXoWh0Vtz++N65/zWM0WZBpzbAe20FRlYNiUsdRETHbTzUDu0p0x4oQqAo04hca+qOtqTeY2AZYNGIjF2ratGw9FNkCy1aVVEM+fx0jLqoHGrt4M1NUv2vXche0wYAkEUU1vumw1FoHrTnJyI6TgiBnfVu+MMyxhTaOPKHeoSBZZAIIXB4ezP2vLYGWT4ZXhGGfspwTLp+4qDM/tp00InNT70Dq0qNMnMxGiaZMe2myQP+vEREJ9vd4IY3FMWYQhtMOgYV6rlBWUuIOofnlY3PQ9n4G9De4MPmV9dCbKrFlk218A9xYMKXqpBTPJABSsCrNmKcKQ9HA8eQN3TWAD4XEVGsmmYvOvxhjMi3ch0gGnBsYelnQW8E1W9vg/+TPbBBixajhBE3zkL5xHxI/Tx8b8V338SIaBY2uY/BXGiHqdCBiddPYYdaIhpQ+5o8cAciKM82I8vC8w31HS8JJQBZVrB3zWHUvb0e2bIGbYggZ85EjL1iBLT6/hnK11jbgS3PLcdQ2KCSVDCoTWi6wIEp143pl/0TER13vI9KMCJjWK4V9jSdt4n6Fy8JJQC1WoXRl5Rj1MVlqN/fgZZX/4Pwim1Yt3wLMLoEk26cBqvj/HrLG6x6qBQFtaFWjLOWYYfnEOZ8bmY/vQIiIqDZHURdRwAAMLrABiPnIaI4YWAZYJIkYchwB4b88Fq42wLY/NoGqHcdwa5HjsGZZ8Osu2fDbO9bk6rfFcYYXREalUYc8tVBN6YCGp5MiOg8RWUFO+rdkBUFuVYDppRygkmKPwaWQWTLMuLSuy9BOBjF9qV7oF+1FZu//yYs8yZh4vyRve7jkldmwzJVK7KEDABQ7z2E7UfHYES+DTrN4A2vJqLUUNfuR7MnCJUkYewQ+2lzqRDFEwNLHOgMGky5biyCV4zAf579AKYVO7D8/S3IvmgcRs8dAaPl3EOiw4EoDmyuh0avQtgjQ6/SoN1hRInDhHe21mNSSQYqcizn3A8RpTdfKIo9jR4AQHGmEVNKHXGuiKh77HSbAI7ubsWO1z+Gvd0PAHA5TBi54AKUjMuF6qRWF58zhP0fH0Tjmu2w+aLQSCp0qBVYxlVg7OfHx6wm/dG+Flw8PDEWkCSixLX5SAfGFNqg1/ByMg0+jhJKUgFPGDuW7UH7xzuQLbRwKmHoJwyF2qiFe9M+ZEZVkIUCl0mNnKoxGDarArYsY7f7anYHcaTdj8klmTGhh4jouCZ3EAdbfZhYnMGFCCkuGFiSnBACDQec2PXmBuiPtgKQ4M80ovjyiaiYWtTj1aKDERl7Gz04/g98/J+6MtcCKyd5IkorsiJwpN0PVyDSdS7IMOlQns3lPCh+GFhSiBxRAKDf1igSQmDT4Q7k2QwodpiwdEcj8u2Grt9JkgQhBASA4kwTcqycFIoo2URlBbsbPIgoClSSBAmASpJQ7DAiwzTwy4YQ9RTnYUkh/b2YoiRJmFrmwK56N9YfaINeq8KEInu3q01vOtyO/c0ezBya3a81EFH/O96iGlUE1CoJowqs7JdCKYWBJU2NLjx3S9SUUgfqnQHsOObC2CH2QaiKiE4lhMDhNj9Ks0wxXywisoJ9TR6Eop2tsDq1CmMKbdBwKDKlKAYWOqvCDCNkRaCm2YPKXGu8y6EBFj24Dit+9BVAAmbfcgt00+8CLLlANy1wNHDafWEcavMBACQARZkmrD/QDp1GheN96DUqFYblWdhZltIG+7BQj9Q0eyFJwFDO7ZJ6FBnKkQ3Yu/RZHPznRhiGmxBodkPXoEXUICAbAVWGDvoMI+z5eSgfX4WsqTcA2cMZZPpRMCLj45pWZJp1cJh0p7WoACf6mRGlCvZhoX5XmWvBwVYfdta7MKaQl4dSRfOKp7Hhpeeh6RCIOiRMuusaDLn2xwAE0FYDpf0Q2g5tReOBnXA3N6HtQB0a1+6DOvh7SMU6TJz/OQSCQahUamh0OuhNVpjtudi15h2E/H44hpRArYTgD0Wg1mhRMfUKmMZfDxiS9ItFyIvwnmXYtvQVNG2rgfDLUNl1KJ46FmPmfxWqslmAum+nVYNWjfJsM2qavZhc0v1U+AwrlM7YwkK94vJHsL/ZA0mSMCzPAtsZhke3eEI40u6HSjpxktWqJZRmmWHRMycnBDmKd28bh5zhuZh6xxNQFU8DVD24vBD2I1rzAT594+do3VwHmNSAACALICKgCgGqITpAAqKuEBCRoHboIGQFpv0yvLky7KMLUTBsFPKHToApfzjqPv0X9CYL8ufcD5izAEUBnIcRPvAfaAw2qLLKAY0BkfpqqHJGQl044dx1RoJA234gZyRQtwGIdC7gh8xSIHvYifsJAchhQK3rvsXIXQ/np69j2/I34d7dAnUQQLEO5TOmIqdoOI7u24Kjn+6AuklGNFNC4ZThKBozFQaTDV5XC9wtDWirOwRPYxuUgAfDZ1+ByjteOOnpBWpbvHAFopAkYHielX8jlDY4rJkGnBACe5s88ASjMOnUGJFnhUatwpr9rbAYNLAbtafN7xCOKth0uANWgwZjCm38thhn4R3/wqqF38Dc3/0FqqLJfduJIseGHDkChL2A8bMWAkUBlAig6Rwev/4Hs9Ba3Qzj0AwEmzxQt3Z2GI1mSFC7BBQNIHSAFBVQhSWIz/qPSgoACchqUqG5MoqccSVoq22AI1+HjjYZF9xwI8y5FXA1HsCete/D29QB2RuBrllAXRGAfMCIqF507Wv+y69CUWmx7jf3oGNXE1QhQFELSDYNjLlWWHJyoNZq0VpzAPLhIIQaMA7LwNg5VyH3gluArKGxx0EIoH4zapY/j/1r1kPuCANRAeglSDoFIgSYmtTIapfQcKkeBd9efeKQCYGh2RbYTZwbidIPAwsNquPDKTv8YVTmWlCUaTrr/T3BCKrrnJhSmgmTjt8k42Xtw5fD09SGec9Vx68vSlttZ8DJG4do3ado+vTvMJjtMFgzYcgohHroJZ2hqHkXAKB523JseutNdDbfBKDIWmQPy4dzTQNkLaAYAEOxFdkV5TCYzXDu3QDtCgHNLSWY8NUlcP/neXy6+K8IWgRUMqAM0WDydQvgKByGoK8DDbU70Xq4Fr42J5SIDEdpIcZecRNMY68BTL1cY0cIKC37seKRGxE5GsDQz12AUdd8A8gfx74/RJ9hYKGksK62DVVDs+JdRnryteLdmy7EjLtvR/b878S7mr5ROlcph6QCmnYC9iLAmBF7H29zZygqnt7ZEiQEcGwz5LYaSDorVJWXAdrul7foW00K0LYfgQPrUL3iL+hYewgiR40rHn4RuooL++95iFIEO91SUlBJwJYjHbAZtSjLMkPNNY8GTfPq5wAJyL7kq/Eupe9OvhSVP7b7+1hyO3+OkySgaArURVP6r47mPWhc+0ds/2glQkc6oPYAQgOIPC2mfPWLyJ//7f4NRURpioGF4mZGRWfriisQwc56F5ST2vpsBg3KssxcuHEgCIEt//wbsqYW9/4yB3UKdKDj45fxyZt/gjgQgGwCTMOyMfHGa1A4eT5UQyaf3tpDROeFgYXizm7UYnxRRsw2lz+CbcdcXbdlRcGoAhv7vPQD5egmiENBTHlgYbxLSS6KjOi+97Hhr0+hfdMRSFHAPCEXM5/4LnRjrga0hnhXSJTSePanhGQ3aTHRlNF1WwiBFbuaML3cwcXbztOOvz8BOVcF7Yh58S4lOQTdaFz+FD7929+gaZAhl2gx5c7/QsHsewFrXryrI0obDCyUFCRJwhWj87D9mAs1zV6oVRIkSYI/FMX0cgfXT+mpSABHPtqO0dde3rM5V9JZ0I26d36E6r++A1UAyJ01FFN//DBUJdM5yocoDhhYKGlIknTapSN/OIod9W5EZQVTSjM5t8uZyBGgfgvqVj4HtU+g4qpvxLuixBX2o+6fP+gMKkGgfP5UjL31p4CtMN6VEaU1BhZKaiadBhOLMxCMyNhwsL2rI29ak6NA/WaEW2pQv2cDDlZvgK+mDWofIFuAiutmnD7xGQFCwLvhD1j9zGJI7QrKr2JQIUokDCyUEgxaNQozjKhr96PYcfaJ61JayIuV94yBarcRAZuAYpVgLnVg8pdvQOG0G4CCCX1e6yaVKU278eFTdyBU7UTmzEJc+PRLDHVECYYX/illZFl0ONjqQ6MrOCjPJ4SAOxiBPxyFLxRFONo5zXyDK4DqOif2N3ngD0cHpZbjGn92AQr/Y0LOdBc+9+Yn+Pzre3DZk2tRuOAnQNGUAQkrixcvhiRJuP/++894nxdffBEXXXQRMjMzkZmZiTlz5mDDhg39Xkuvhbyo/cNXsfTO6xBo9eLyp3+OCx/5gGGFKAHxqxalDL1GDYNWjYis9OpxQghU1zk7/z8ACT1fFdei10ARAhKAUFSBNxTFkAwjJhZnwBeK4nCbH/6wjCyzDmWnrK00EEI+FwALtCplUOYB2bhxI1544QWMHz/+rPdbvXo1br75ZsycORMGgwFPPPEE5s6di507d2LIkCEDXmd3lMadeO/e6yEFgDFfno+yLyzm0GSiBMbAQimjtsULlQTkWPU9fow3FMXHNa2YVZkNcz+vkGvWazCqwAZvKIpVe5oHJbAUTFuA2jdXoLbRjBH+9gGdGM7r9eKWW27Biy++iEcfffSs9/3zn/8cc/ull17Cm2++iZUrV+K2224bsBq7pSiI7n8fm/7wPag9wPw//St29WYiSki8JEQpY3ieFVNKM7HjmAvrD7QhEJbPev8dx1zY3+TB3NF5/R5WTrblSAeKM42ornNia50TO465UO8MQFb6fxkvl8qGkAYo/1SPDx6YAnQc6vfnOO7uu+/GVVddhTlz5vT6sX6/H5FIBA7HIM60GwnC+cEv8d7/jMf799yL1gY/Jt//3wwrREmCLSyUUiRJwtQyBxRFYNsxFxQhICsCDrMOQ3MsAIC6dj/q2v0oyjShJGvgO+heNCwn5nZUVtDkCWFXvRtRRem6/HS2i1Bnijb5NgPybPqufeR8/hE0b34XeC0I9VY9PrzqSlzy7lIgs+z8X8hJXnvtNWzevBkbN27s0+MfeughFBYW9ins9JocQcuKn+GT378CdYeAbVohqr77I6jLZ3E+FaIkwsBCKUmlkjCxOKPrdosnhPUH2qAoAhU5FsyszI5bbRq1CkMyjBiScX4L4gkh0OQOYetRV8z2rK+vQtGtW6B/7ZsI/SmANd+9CKWXfRGFYy+FuuJiQG89r+etq6vDfffdhxUrVsBg6H2fj8WLF+O1117D6tWr+/T43oge3oD3F38F4kAIBXOGY8qdvwCyKwf0OYloYEhCiP5vlx5kvVmemijVtXhCOOYMQNu0FYd+ehdUOgVyUAu1B4hagcu++R1Ypt/W59aFt956CwsWLIBafWKmXFmWIUkSVCoVQqFQzO9O9tRTT+HRRx/F+++/j6lTp/bp+Xsk7MOhX38eu5fXQzXUiDmLXoS6eNrAPR8R9UlvPr8ZWIjSgRBA+wFseOHr6Fh1COaJBsx68DUgd1Svd+XxeHD48OGYbXfeeSdGjhyJhx56CGPHju32cU8++SQee+wxLFu2DBdccEGfXkaP+Nvx4cKJyF1thunbVSj98guAWjtwz0dEfdabz292uiVKB5IEZA3F9EVLceF3vgLXngCW3nodvJ/+pde7slqtGDt2bMyP2WxGVlZWV1i57bbbsGjRoq7HPPHEE/j+97+P3/3udygrK0NjYyMaGxvh9Xr77SUCQGDH2/jX/1wIT6sRQ1++B6V3/I5hhShFMLAQpRNJguXyb+Gqv1dDdsg4/MnbA/I0R44cQUNDQ9ft5557DuFwGF/4whdQUFDQ9fPUU0/1zxMG3dj802vw4QPfgq0kE59/eRV0F97dP/smooTATrdEaShyrBrCr0JjbQ3G9MP+Vq9efdbbhw4d6odn6Z5cvw1Lv3MzhDOKC797DzIvuYejf4hSEAMLURra9JdHAb3Apd94Md6lnJfw/g+w/MGvQltgwBVPvQ1VNqfUJ0pVvCRElGbkpj1o/aQG9lHFUA+ZGO9y+sy78VWsuP+rsI3Mwryf/4dhhSjFsYWFKM1IvmY46tWYtujmeJfSN3IEW355I5r+vQt5l5dj6rf+CWh6vhwDESUntrAQpRn3wU/hzFGgHXNNvEvpk8Dm12H47R6Iggim3vlTQMVRQETpgIGFKI0orbVY8+sXkH/ZcMCaF+9y+sQ4YQFMXy+F7NSg+oobsex/RsS7JCIaBAwsROki7MeqH38BUoYGk+/987nvn7AkmIZdDMmmQkOhgklXfSHeBRHRIGAfFqJ0EHDiPz/6HEIH/Jj7qyWAIQlnhA504Mg7j2Lrm+9C7RHIuagCU+94EqqCcfGujIgGAQMLUYqTj1Vj2fdugeKKYu5Tz0JbPjPeJfWOpxH7/vod7PvXx5BkoHTORIy/dTHgKI93ZUQ0iBhYiFKY86MX8PGTP4e21IA5P/0nVMm0UnHHYWz9/TdwdOV2CC0w8ppLUPlfjwKW3HhXRkRxwMBClIqiYez67Z2o+/unKJw/EpPu/QugM8W7qp6JBHDg9W9i92vvQ7FImHz7dRjy+e8ABnu8KyOiOGJgIUo1rmNY9cNrENzrxbRvfQU5c7+ZNFPVh3cvw4onFwLNUYz64hxU3PQkoDPHuywiSgAMLEQpJLx7GZY/fB+gk3Dlb/4ATdmMeJfUM/52VD9/Fxr/vQumiXZc8sQfocrlcGUiOoGBhSgVCIFj//gutr3wJmxTsnDxd98GzNnxrurchIB3wx+w+hePA2GBqof+H7Iuvx9QccYFIorFwEKU7IIufPLTG9DxUR2GfflyVN76DKBSx7uqc1Lqt+E/z3wdwQ0tyLm4GDPu/yNgK4h3WUSUoBhYiJKY0nYAy759DeSWCC5d/CNYptwU75LOTZHR9N6j+PS5V4FcDS594ocwT0nSdY2IaND0qt31ueeew/jx42Gz2WCz2VBVVYV///vfXb+vra3FggULkJOTA5vNhhtvvBFNTU3n3O+zzz6LsrIyGAwGzJgxAxs2bOj9KyFKM/LRTXjv7qsgZIHPvfivpAgrytHNWHH/NGz51asov3oarnpxC8MKEfVIrwJLUVERFi9ejE2bNuHTTz/F5ZdfjmuvvRY7d+6Ez+fD3LlzIUkSVq1ahY8//hjhcBhXX301FEU54z5ff/11LFy4EA8//DA2b96MCRMmYN68eWhubj7vF0eUqsI1q/Hvu78EQ54Rn/vVaqhyhsW7pDNSGnZg+7NfwtK7J2H5f9+MaDCCOc//DqO/+idAo4t3eUSUJCQhhDifHTgcDvz0pz9FcXEx5s+fj46ODthsndN+u1wuZGZmYvny5ZgzZ063j58xYwamTZuGZ555BgCgKAqKi4tx77334tvf/naPanC73bDb7XC5XF3PTZSq5GNb8O97boZ1RAYueeR9QG+Jd0ln1LF8MY7e/3scGR+BbXgpJs2/FZbptwJqrrBMRL37/O5zV3xZlvHaa6/B5/OhqqoKoVAIkiRBr9d33cdgMEClUmHNmjXd7iMcDmPTpk0xYUalUmHOnDlYt25dX0sjSl2BDixd9CXohhhwyQ+XJ3RYAQBbyUQcK1Kgsetx0bf+DEvVnQwrRNQnvQ4s27dvh8VigV6vx1e/+lX84x//wOjRo3HBBRfAbDbjoYcegt/vh8/nwze/+U3IsoyGhoZu99Xa2gpZlpGXF7vMfV5eHhobG89YQygUgtvtjvkhSgcbf3kzFK+CuY++kxQLGKoLxqLsyjJkr1Nw+K1H4l0OESWxXgeWESNGoLq6Gp988gm+9rWv4fbbb8euXbuQk5ODN954A++88w4sFgvsdjucTicmT54MVT/PqfD444/Dbrd3/RQXF/fr/okSUXjv+2hfcQiXLPwmkJHA73k5iuje5fj4h7Px3pdmo2btIdjuvxClNzwW78qIKIn1elizTqdDZWXnAmpTpkzBxo0b8ctf/hIvvPAC5s6di9raWrS2tkKj0SAjIwP5+fmoqKjodl/Z2dlQq9WnjSRqampCfn7+GWtYtGgRFi5c2HXb7XYztFDKW/no/0K2aGCbeVe8SzmdHIFcswrV7zyH+o17oO0QUIq1mH7vHci+7B5Ab413hUSU5M57HhZFURAKhWK2ZWd3zrC5atUqNDc345prrun2sTqdDlOmTMHKlStx3XXXde1v5cqVuOeee874nHq9PqavDFHK6zgEdb0O0x+8M3FmgY2GEd2/Elve+Q0aP90PrVNALlBj+NxZGDH/bqBgYtKsYUREia9XgWXRokWYP38+SkpK4PF48Oqrr2L16tVYtmwZAGDJkiUYNWoUcnJysG7dOtx333144IEHMGLEiTVBZs+ejQULFnQFkoULF+L222/H1KlTMX36dDz99NPw+Xy48847+/FlEiW3Tb+9G2GHgqzL7o1vIdEwInuXYsvbL6BpUw20bkAeosGoz12CyrlfAwomMKQQ0YDoVWBpbm7GbbfdhoaGBtjtdowfPx7Lli3DFVdcAQDYu3cvFi1ahPb2dpSVleG73/0uHnjggZh9HL9kdNxNN92ElpYW/OAHP0BjYyMmTpyIpUuXntYRlyidtdXUQm2WAJ0pPgU4j6Dmn49j978/gLZdQC7SYvQ1czB07teAvDEMKUQ04M57HpZEwHlYKJU5P3oen/zoF5jy0P8i+4pvDN4TC4HI3qVY+4fH4atugmwAyi6fjHH/9b3OkEJEdJ568/nNtYSIEpjcsB0fP/kLDPncKGTPWXjuB/RWyAvUrupsuYkEgJKZgDETga1/w0cv/QRiXwCiQo+qb34VmRf+T8LP+0JEqYuBhSiBLfvOjZAEMPGeP/fPZZeAE/Khj7HvozdwcEs11PuDKDkmoa5AQNYJyGbAmBWEdrsR2pk2XPTsk9AOu4KXfIgo7hhYiBJYTkUeXAcb8e7/mwFjbgb0ZjM0Oi0iwSCi4QjkaBR6swlloyagaNwlgKTuDBdCIORsQHvjQbTXH0JDbQ2CjS6oOhRIMhDNViFrZAnGfOEK2NVhjBp1DWCwYcefH0LTX7cgYAbmPfIOYGVfMiJKDOzDQpTgorUfYfMbT8LT3oGIPwglKkOt00Kt1UClViPsDyBS74U6cOIxkgAUNSD0ACxqmAuzUDh8JMrHXwJdeRXgqDhzq0nQDajUgM48KK+PiNJXbz6/GViIUkE0DIQ8AAQgFECOAKYsQGuId2VERGfETrdE6UajAzRZ8a6CiGjAJMiUmURERERnxsBCRERECY+BhYiIiBIeAwsRERElPAYWIiIiSngMLERERJTwGFiIiIgo4TGwEBERUcJjYCEiIqKEx8BCRERECY+BhYiIiBIeAwsRERElPAYWIiIiSngpsVqzEAJA5zLVRERElByOf24f/xw/m5QILB6PBwBQXFwc50qIiIiotzweD+x2+1nvI4mexJoEpygK6uvrYbVaIUlSvMs5jdvtRnFxMerq6mCz2eJdTtzxeJzAYxGLx+MEHotYPB4npNKxEELA4/GgsLAQKtXZe6mkRAuLSqVCUVFRvMs4J5vNlvRvrv7E43ECj0UsHo8TeCxi8XickCrH4lwtK8ex0y0RERElPAYWIiIiSngMLINAr9fj4Ycfhl6vj3cpCYHH4wQei1g8HifwWMTi8TghXY9FSnS6JSIiotTGFhYiIiJKeAwsRERElPAYWIiIiCjhMbAQERFRwmNg6aXVq1dDkqRufzZu3AgAOHToULe/X79+/Vn33d1jXnvttdOef/LkydDr9aisrMQrr7wyUC+1RwbqeGzduhU333wziouLYTQaMWrUKPzyl7/s0XM3NjYO6Gs+k4F8bxw5cgRXXXUVTCYTcnNz8a1vfQvRaPS050+298bJampqYLVakZGRcdb9vvLKK2fcb3Nz81mfO5HfGyfr6bEAUve8cbKeHo9UPW+crDfvjWQ8b5yVoF4JhUKioaEh5ucrX/mKKC8vF4qiCCGEOHjwoAAg3n///Zj7hcPhs+4bgFiyZEnMYwKBQNfvDxw4IEwmk1i4cKHYtWuX+PWvfy3UarVYunTpgL7msxmo4/Hyyy+L//u//xOrV68WtbW14o9//KMwGo3i17/+ddd9PvjgAwFA7N27N2a/siwP+OvuzkAdi2g0KsaOHSvmzJkjtmzZIt577z2RnZ0tFi1a1HWfZH1vHBcOh8XUqVPF/Pnzhd1uP+t+/X7/afudN2+euOSSS7ruk4zvjeN6cyyESN3zxnG9OR6pet44rjfHIlnPG2fDwHKewuGwyMnJET/60Y+6th3/UNqyZUuv9gVA/OMf/zjj7x988EExZsyYmG033XSTmDdvXq+eZyD15/E41de//nVx2WWXdd0+fuLp6Og4r/0OlP46Fu+9955QqVSisbGxa9tzzz0nbDabCIVCQojkfW8c9+CDD4pbb71VLFmypEcf0idrbm4WWq1W/OEPf+jalozvjeN6eyxS9bxx3Pm8N4RIjfPGcb05Fqly3jgZLwmdp7fffhttbW248847T/vdNddcg9zcXMyaNQtvv/12j/Z39913Izs7G9OnT8fvfve7mCW3161bhzlz5sTcf968eVi3bt35vYh+1N/H42QulwsOh+O07RMnTkRBQQGuuOIKfPzxx32qeyD017FYt24dxo0bh7y8vK5t8+bNg9vtxs6dO7vuk6zvjVWrVuGNN97As88+26f9/uEPf4DJZMIXvvCF036XbO+Nvh6LVD1vnO97A0id80Zvj0WqnDdOlhKLH8bTyy+/jHnz5sUsvmixWPCzn/0MF154IVQqFd58801cd911eOutt3DNNdeccV8/+tGPcPnll8NkMmH58uX4+te/Dq/Xi//7v/8DADQ2Nsa8+QAgLy8PbrcbgUAARqNxYF5kL/Tn8TjZ2rVr8frrr+Pdd9/t2lZQUIDnn38eU6dORSgUwksvvYRLL70Un3zyCSZPntzvr623+utYnOnf/fjvznafRH9vtLW14Y477sCf/vSnPi/i9vLLL+NLX/pSzGtMxvdGX49Fqp43+uO9kSrnjb4ci1Q5b8SIdxNPonjooYcEgLP+7N69O+YxdXV1QqVSib/97W/n3P+Xv/xlMWvWrF7V9P3vf18UFRV13R42bJj4yU9+EnOfd999VwAQfr+/V/s+l0Q6Htu3bxfZ2dnixz/+8Tnve/HFF4tbb721R/vtqXgfi//5n/8Rc+fOjdnm8/kEAPHee+8JIZL3vbFgwQLx0EMPdd3ubbP/2rVrBQDx6aefnvO+if7eON9jcVyqnDfO93ik0nmjL8ci0c4b/YEtLJ/5xje+gTvuuOOs96moqIi5vWTJEmRlZfWolWDGjBlYsWJFr2qaMWMGfvzjHyMUCkGv1yM/Px9NTU0x92lqaoLNZuv3JJwox2PXrl2YPXs2/vd//xff+973znn/6dOnY82aNee8X2/E+1jk5+djw4YNMduOvw/y8/O7/puM741Vq1bh7bffxlNPPQUAEEJAURRoNBr89re/xX//93+f9XleeuklTJw4EVOmTDln3Yn+3jjfY3Fcqpw3zud4pNp5oy/HItHOG/2BgeUzOTk5yMnJ6fH9hRBYsmQJbrvtNmi12nPev7q6GgUFBb2qqbq6GpmZmV0LXFVVVeG9996Luc+KFStQVVXVq/32RCIcj507d+Lyyy/H7bffjscee6xHdfTlOJ9LvI9FVVUVHnvsMTQ3NyM3NxdA57+7zWbD6NGju+6TjO+NdevWQZblrtv//Oc/8cQTT2Dt2rUYMmTIWffr9Xrx17/+FY8//niP6kj098b5HIuTpcp5o6/HIxXPG305Fol23ugXcWrZSXrvv/9+t016QgjxyiuviFdffVXs3r1b7N69Wzz22GNCpVKJ3/3ud133+fvf/y5GjBjRdfvtt98WL774oti+fbvYv3+/+M1vfiNMJpP4wQ9+0HWf40PQvvWtb4ndu3eLZ599NmGGoPX38di+fbvIyckRt956a8xwv+bm5q77/OIXvxBvvfWW2L9/v9i+fbu47777hEqlEu+///7Avthz6O9jcXx44ty5c0V1dbVYunSpyMnJ6XZ4YrK9N07VXVP3qcfjuJdeekkYDIZuR3sk43vjVD05Fql83jhVT45Hqp43TtWTY5Hs543uMLD00c033yxmzpzZ7e9eeeUVMWrUKGEymYTNZhPTp08Xb7zxRsx9lixZIk7Oi//+97/FxIkThcViEWazWUyYMEE8//zzp80N8MEHH4iJEycKnU4nKioqxJIlS/r9tfVFfx+Phx9+uNtrvqWlpV33eeKJJ8TQoUOFwWAQDodDXHrppWLVqlUD8vp6o7+PhRBCHDp0SMyfP18YjUaRnZ0tvvGNb4hIJBJzn2R8b5yquxNxd8dDCCGqqqrEl770pW73k4zvjVP15Fik8nnjVD05Hql63jhVT/9Okvm80R1JiJPGvxERERElIM7DQkRERAmPgYWIiIgSHgMLERERJTwGFiIiIkp4DCxERESU8BhYiIiIKOExsBAREVHCY2AhIiKihMfAQkRERAmPgYWIiIgSHgMLERERJTwGFiIiIkp4/x/UJndx3x2jqQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#For corners and outcroppings, we fuse county clusters\n",
    "print(\"Now finalize the map topology before any squish operations.  Plot countyPop/aDP\")\n",
    "preSquishCountyGeom = [countyGeom[c] for c in range(nCounties)]\n",
    "maxD = 0.\n",
    "for c in range(nCounties):\n",
    "    if c%20 == 0:\n",
    "        print(\"Working on county \",c,\"distances\")\n",
    "    if c not in cutCountyList:\n",
    "        plotPoly(countyGeom[c],0.2)\n",
    "        plotCenter(r3(countyPop[c]/aDP), countyGeom[c], 7 )\n",
    "        for cc in range(c+1, nCounties):\n",
    "            dist = getLongDist(countyCP[c],countyCP[cc],xScale)\n",
    "            if dist > maxD and cc not in cutCountyList:\n",
    "                maxD = dist\n",
    "                #print(c,cc,maxD)\n",
    "print(\"the max LAT-scaled distance between counties is\",r5(maxD))\n",
    "plotPoly(MAP)\n",
    "plotPoly(MAP.centroid.buffer(0.5*maxD))\n",
    "plt.show()\n",
    "inputD = float( input(\"enter user-picked max district diameter, or 0 to accept \"+str(r5(maxD))+\" \") )\n",
    "if inputD > 0:\n",
    "    maxD = inputD\n",
    "neighborCountyList = [list() for c in range(nCounties)]\n",
    "for c in uncutCountyList:\n",
    "    if c%20 == 0:\n",
    "        print(\"Working on county \",c,\"neighbors\")\n",
    "    for cc in uncutCountyList:\n",
    "        if cc > c and cc not in cutCountyList:  \n",
    "            if countyGeom[c].intersects(countyGeom[cc]) :\n",
    "                neighborCountyList[c].append(cc)\n",
    "                neighborCountyList[cc].append(c)\n",
    "print(\"I have also identified each county's neighbors.  Let's visualize the counties with two or fewer neighbors\")\n",
    "hasFewNeighborCs, has1neighborCs = list(), list()\n",
    "plotPoly(MAP,0.15)\n",
    "for c in uncutCountyList:\n",
    "    if len(neighborCountyList[c]) == 2:\n",
    "        hasFewNeighborCs.append(c)\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c+0.2,countyGeom[c])\n",
    "        for cc in neighborCountyList[c] :\n",
    "            plotPoly(countyGeom[c],0.5)\n",
    "    if len(neighborCountyList[c]) < 2:\n",
    "        has1neighborCs.append(c)\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c+0.1,countyGeom[c])\n",
    "        for cc in neighborCountyList[c] :\n",
    "            plotPoly(countyGeom[c],0.2)\n",
    "plt.show()   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f9b3df93-d821-44ca-b4f4-b65d13baaffb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "continuing from above, develop corner county blocks from each low-pop corner county until it hits 0.25 of 774082\n",
      "checking if county 4 with pop 95263.0 and 1 or 2 neighbors is less pop than 193520\n",
      "checking if county 16 with pop 64837.0 and 1 or 2 neighbors is less pop than 193520\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Below I plot these again by county no, with faded neighboring counties\n",
      "0   [4]\n",
      "1   [16]\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now finalize the corner lists.  Remember, our avgDistrictPop and normal pop threshold are 774082.833 193520\n",
      "You may suggest [ [4], [16] ] \n",
      "let's decide whether to delete, accept, or modify list [4] with pop 95263.0\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 0 to ax, 1 to accept, or type in a [replacement list] (must start with same c as orig list) 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "let's decide whether to delete, accept, or modify list [16] with pop 64837.0\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 0 to ax, 1 to accept, or type in a [replacement list] (must start with same c as orig list) 1\n",
      "enter 1 if you want to manually add another corner-county cluster 0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Our final pops and fused-county lists are...\n",
      "95263.0 [4]\n",
      "64837.0 [16]\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "aDP = float(statePop)/nDistricts\n",
    "maxCCBratio = 1./4.  #adjustable max fraction of district pop for corner county blocks.  Let's try 3/16\n",
    "maxCCBpop = maxCCBratio * aDP\n",
    "print(\"continuing from above, develop corner county blocks from each low-pop corner county until it hits\",r3(maxCCBratio),\"of\",int(aDP) )\n",
    "CCBlist, CCBpop, passThruList = list(), list(), list()  #\"waiveThru\" counties get chance to join a cluster even if high pop\n",
    "nFuses = 0\n",
    "for c in has1neighborCs:\n",
    "    print(\"checking if county\",c,\"with pop\",countyPop[c],\"and only 1 neighbor is less pop than\",int(maxCCBpop),\"vs districtPop\",int(aDP) )\n",
    "    if countyPop[c] > maxCCBpop:\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c,countyGeom[c])\n",
    "        nc = neighborCountyList[c][0]\n",
    "        plotPoly(countyGeom[nc],0.5)\n",
    "        plotPoly(MAP,0.2)\n",
    "        print(\"county\",c,\"has pop\",countyPop[c],\"and its only neighbor has pop\",countyPop[nc],\"vs districtPop\",aDP,\". Default = keep un-fused\")\n",
    "        print(\"enter 0 to keep\",c,\"as an unfused collection of units, 1 to fuse as one unit and stop, 2 to force-add at least the next closest county\")\n",
    "        fuseChoice = input(\"0, 1, or 2.  Any other input taken as a zero\")\n",
    "        if fuseChoice == 0:\n",
    "            keepUnfused = True\n",
    "            break\n",
    "        elif int(fuseChoice) == 1:\n",
    "            CCBlist.append([c])\n",
    "            CCBpop.append(countyPop[c])  \n",
    "            hasFewNeighborCs.append(c)  #this adds this [c] to the final list of fused units, but will fail to find more in below\n",
    "        elif int(fuseChoice) == 2:\n",
    "            CCBlist.append([c,nc ] )\n",
    "            CCBpop.append(countyPop[c] + countyPop[nc])\n",
    "            hasFewNeighborCs.append(c)\n",
    "            passThruList.append(c)   #pass on thru to the below 2neighbor logic even if too high-pop to qualify\n",
    "    else:\n",
    "        hasFewNeighborCs.append(c)  #normal case; we'll handle in next, more general, for loop            \n",
    "        \n",
    "for c in hasFewNeighborCs:\n",
    "    print(\"checking if county\",c,\"with pop\",countyPop[c],\"and 1 or 2 neighbors is less pop than\",int(maxCCBpop) )\n",
    "    if countyPop[c] < maxCCBpop :\n",
    "        CCBlist.append([c])\n",
    "        CCBpop.append(countyPop[c])\n",
    "        CCBno = CCBlist.index([c])\n",
    "    if c in passThruList:\n",
    "        CCBno = CCBlist.index([c,neighborCountyList[c][0] ])\n",
    "    if countyPop[c] < maxCCBpop or c in passThruList:            \n",
    "        CCBstarter = c\n",
    "        canAdd = True\n",
    "        while canAdd:\n",
    "            nbrSet = set()\n",
    "            for cc in CCBlist[CCBno]:\n",
    "                nbrSet = ( nbrSet.union(set(neighborCountyList[cc])) ).difference(set(CCBlist[CCBno]))\n",
    "            nPop = [countyPop[cc] for cc in nbrSet]\n",
    "            nDist = [countyGeom[cc].centroid.distance(countyGeom[CCBstarter].centroid) for cc in nbrSet]\n",
    "            idx = np.argsort(nDist)\n",
    "            nbrList, newList = list(nbrSet), list()\n",
    "            for i in range(len(nDist)):  #add counties, closest to starter that will fit until over\n",
    "                cc = nbrList[idx[i]]\n",
    "                if CCBpop[CCBno] + countyPop[cc] < maxCCBpop:\n",
    "                    newList.append(cc)\n",
    "                    CCBlist[CCBno].append(cc)\n",
    "                    CCBpop[CCBno] += countyPop[cc]\n",
    "                    #print(\"adding county\",cc,\"with pop\",countyPop[cc],\"to list started by\",CCBstarter,\".Cluster pop now\",CCBpop[CCBno]  )\n",
    "            if newList == list():  #no eligible neighbor counties found; stop\n",
    "                canAdd = False\n",
    "                for cc in CCBlist[CCBno]:\n",
    "                    plotPoly(countyGeom[cc])\n",
    "                    plotCenter(CCBno,countyGeom[cc])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()\n",
    "                    \n",
    "print(\"Below I plot these again by county no, with faded neighboring counties\")\n",
    "plotPoly(MAP,0.15)\n",
    "for L in CCBlist:\n",
    "    print(CCBlist.index(L),\" \",L)\n",
    "    for c in L:\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c,countyGeom[c])\n",
    "        for cc in list(set(neighborCountyList[c]).difference(L) ):\n",
    "            plotPoly(countyGeom[cc],0.4)\n",
    "            plotCenter(cc,countyGeom[cc],8)\n",
    "plt.show()\n",
    "rejectList = list()\n",
    "print(\"Now finalize the corner lists.  Remember, our avgDistrictPop and normal pop threshold are\",r3(aDP), int(maxCCBpop))\n",
    "print(\"You may suggest [ [4], [16] ] \" )\n",
    "for i,L in enumerate(CCBlist):\n",
    "    if L[0] not in passThruList:  #if we forced the fused-counties list above, don't give option here to modify\n",
    "        print(\"let's decide whether to delete, accept, or modify list\",L,\"with pop\",CCBpop[i] )\n",
    "        isOK = input(\"enter 0 to ax, 1 to accept, or type in a [replacement list] (must start with same c as orig list)\")\n",
    "        if not (isOK == 1 or isOK == str(1)) :\n",
    "            if isOK == 0 or isOK == str(0) :\n",
    "                rejectList.append(L)\n",
    "            else:\n",
    "                notGood = True\n",
    "                while notGood:       \n",
    "                    Lnew = ast.literal_eval(isOK)        \n",
    "                    if len(list(set(Lnew).difference(set([c for c in range(nCounties) ] )))) == 0:\n",
    "                        notGood = False\n",
    "                    else:\n",
    "                        print(\"Oops!  You didn't enter a valid list.  Try again as [\",L[0],\", n1, n2, ... ] where n1, n2 are county integers\")\n",
    "                        isOK = input(\"Try again here \")\n",
    "                print(\"OK, I will replace\",L,\"with\",Lnew)\n",
    "                CCBpop[i] = np.sum( [countyPop[c] for c in Lnew] )\n",
    "                CCBlist[i] = Lnew.copy()\n",
    "for L in rejectList:\n",
    "    del CCBpop[ CCBlist.index(L)]\n",
    "    del CCBlist[CCBlist.index(L)]\n",
    "stillAdding = True\n",
    "while stillAdding:\n",
    "    addMore = input(\"enter 1 if you want to manually add another corner-county cluster\")\n",
    "    if int(addMore) != 1:\n",
    "        stillAdding = False\n",
    "    else:\n",
    "        isOK = input(\"Type in a [county list], where the corner county is first in the list.  Or type 0 to stop\")\n",
    "        if isOK == 0 or isOK == str(0) :\n",
    "            print(\"OK, we'll stop adding corner clusters\")\n",
    "            stillAdding = False\n",
    "        else:\n",
    "            notGood = True\n",
    "            while notGood:       \n",
    "                Lnew = ast.literal_eval(isOK)        \n",
    "                if len(list(set(Lnew).difference(set([c for c in range(nCounties) ] )))) == 0:\n",
    "                    notGood = False\n",
    "                    for L in CCBlist:\n",
    "                        if set(L).intersection(set(Lnew)) != set(list()) :\n",
    "                            notGood = True\n",
    "                            print(\"OOPS! The following inputted counties are already in\",L,\":\",set(L).intersection(set(Lnew)) )\n",
    "                            isOK = input(\"Try again here \")\n",
    "                    if notGood == False:\n",
    "                        CCBlist.append(Lnew)\n",
    "                        CCBpop.append( np.sum( [countyPop[c] for c in Lnew] ) )\n",
    "                else:\n",
    "                    print(\"Oops!  You didn't enter a valid list.  Try again as [\",L[0],\", n1, n2, ... ] where n1, n2 are county integers\")\n",
    "                    isOK = input(\"Try again here \")\n",
    "print(\"Our final pops and fused-county lists are...\")\n",
    "allFusedCounties = list()\n",
    "CCBgeom = [dummyPoly for L in CCBlist ]\n",
    "CCBcp = list()\n",
    "for i, L in enumerate(CCBlist):\n",
    "    CCBcp.append( getHDcp([countyCP[c] for c in L], [countyPop[c] for c in L], [ j for j in range(len(L)) ] ) )\n",
    "    print(CCBpop[i],L)\n",
    "    pops, CPs = list(), list()\n",
    "    for c in L:\n",
    "        if c == L[0]:\n",
    "            CCBgeom[i] = countyGeom[c]\n",
    "        else:\n",
    "            CCBgeom[i] = CCBgeom[i].union(countyGeom[c])\n",
    "        allFusedCounties.append(c)\n",
    "        pops += countyPop[c]       #  IS THIS EVEN USED?\n",
    "        CPs.append(countyCP[c])   #  IS THIS EVEN USED?\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(i,countyGeom[c])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "206c9372-8ec8-4190-93ed-04df286466e0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now identify the border counties + border fused units, and interior small counties with pop < 15481\n",
      "We defined a total of 0 unit (but not corner-cluster) counties in the map, excluding the cut-out districts\n"
     ]
    }
   ],
   "source": [
    "maxWholeBorderCountyPop = 0.02 * aDP   #to encourage contiguity, border counties > 0.02 aDP will be forced whole\n",
    "maxInteriorBorderCountyPop = 0.02 * aDP\n",
    "print(\"now identify the border counties + border fused units, and interior small counties with pop <\", int(maxInteriorBorderCountyPop))\n",
    "unitCounties, borderCounties = list(), list()\n",
    "origMAP = MAP\n",
    "if MAP.geom_type == dummyPoly.geom_type:\n",
    "    MAPexterior = MAP.exterior\n",
    "else:\n",
    "    maxArea = 0\n",
    "    for geo in MAP.geoms:\n",
    "        if geo.area > maxArea:\n",
    "            MAPexterior = geo.exterior\n",
    "            maxArea = geo.area\n",
    "            MAP0 = geo\n",
    "    MAP = MAP0\n",
    "for c in uncutCountyList:\n",
    "    if countyGeom[c].intersects(MAPexterior):\n",
    "        borderCounties.append(c)\n",
    "        if c not in allFusedCounties:\n",
    "            if countyPop[c] < maxWholeBorderCountyPop:\n",
    "                unitCounties.append(c)\n",
    "    else:\n",
    "        if countyPop[c] < maxInteriorBorderCountyPop and c not in allFusedCounties:\n",
    "            unitCounties.append(c)\n",
    "print(\"We defined a total of\",len(unitCounties),\"unit (but not corner-cluster) counties in the map, excluding the cut-out districts\")        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e0ff719c-59dc-4827-a522-11bd352f7524",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For this state, do we have a lot of populated fragmented VTDs?\n",
      "19 fragmented VTDs out of 6361\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FYI, here are the locations of fragmented VTDs with pop > 3000\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"For this state, do we have a lot of populated fragmented VTDs?\")\n",
    "nFragmentedVTDs,fragmentedVTDs = 0, list()\n",
    "for v in populatedTractList:\n",
    "    c = countyNo[v]\n",
    "    if c not in allFusedCounties and c not in unitCounties: \n",
    "        if vtdGeom[v].geom_type != dummyPoly.geom_type :  #a multipoly vtd-based unit\n",
    "            nFragmentedVTDs +=1\n",
    "            fragmentedVTDs.append(v)\n",
    "print(len(fragmentedVTDs),\"fragmented VTDs out of\",nVTDs)\n",
    "fragPop = [tractPop[v] for v in fragmentedVTDs]\n",
    "plt.hist(fragPop)\n",
    "plt.show()\n",
    "print(\"FYI, here are the locations of fragmented VTDs with pop > 3000\")\n",
    "for v in fragmentedVTDs:\n",
    "    if tractPop[v] > 3000:\n",
    "        plotPoly(vtdGeom[v])\n",
    "plotPoly(MAP,0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "71d771f8-dbe2-48f9-a702-9f66a62d1174",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now writing the master list of units, which may be individual vtd's (+surrounds), whole counties, or corner county clusters\n",
      "I split up 19 fragmented VTDs. Now define unit neighbor lists and fuse geometries of surrounds.\n",
      "looking for surrounds, now working on vtd 0\n",
      "looking for surrounds, now working on vtd 500\n",
      "looking for surrounds, now working on vtd 1000\n",
      "looking for surrounds, now working on vtd 1501\n",
      "looking for surrounds, now working on vtd 2002\n",
      "looking for surrounds, now working on vtd 2503\n",
      "looking for surrounds, now working on vtd 3003\n",
      "looking for surrounds, now working on vtd 3503\n",
      "looking for surrounds, now working on vtd 4003\n",
      "looking for surrounds, now working on vtd 4503\n",
      "looking for surrounds, now working on vtd 5003\n",
      "looking for surrounds, now working on vtd 5504\n",
      "looking for surrounds, now working on vtd 6004\n",
      "visualizing VTD fragments in county 18\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the [v1, v2, ...] list of surrounded fragVTDs from above map [1710, 1715]\n",
      "enter the fragVTDno that surrounds these 1709\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "special for NJ , I believe that [1710, 1715] are surrounded by vtd (fragment) 1709 . Here, let me show you\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 to apply the surrounding operation 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "After surround checks, we appear to have 6199 building blocks defined. We captured 7 surrounded VTDs\n",
      "working on unit neighbor lists for county 0\n",
      "working on unit neighbor lists for county 20\n",
      "All done creating unit lists\n"
     ]
    }
   ],
   "source": [
    "#3/2/24 - split up all multipoly VTDs into fragments, divvy pop by area\n",
    "unitPop, unitCP, unitGeom, nbrUnitGeom, allUnits = list(), list(), list(), list(), list()\n",
    "vtdUnits, countyUnits, borderUnits = list(),list(),list()\n",
    "countyUnitList = [list() for c in range(nCounties) ]\n",
    "surroundedVTDs, surrounders = list(), list()  #vtds that are surrounded by another vtd - problem for later enclaves, xfer their pops to surrounders\n",
    "#These surrounded VTDs don't get transferred to the unit list\n",
    "print(\"Now writing the master list of units, which may be individual vtd's (+surrounds), whole counties, or corner county clusters\")\n",
    "for c in unitCounties:\n",
    "    unitCP.append(countyCP[c])\n",
    "    unitPop.append(countyPop[c])\n",
    "    unitGeom.append(   countyGeom[c] )\n",
    "    nbrUnitGeom.append(countyGeom[c] )\n",
    "    countyUnits.append(c)\n",
    "    allUnits.append(c+0.5)  #use non-integers to avoid vtd and county and cluster confusion\n",
    "\n",
    "nVTDneighbors = [0 for v in range(nVTDs)] #this loop -- just checking for surrounded VTDs\n",
    "lastVTDneighbor = [-999 for v in range(nVTDs)]\n",
    "\n",
    "nFragmentedVTDs,fragmentedVTDs, coastalFragmentedVTDs = 0, list(), list()  #a prev version treated coastal separately\n",
    "fragVTDgeom, parentVTDno, fragVTDpop = vtdGeom.to_list(), [v for v in range(nVTDs)], tractPop.to_list()  #these lists will expand to include vtd fragments \n",
    "origVTDgeom = vtdGeom.copy() #we create a parallel fragVTDgeom list which grabs the 1st fragment, then append fragments to the total list\n",
    "origVTDpop = tractPop.copy()\n",
    "VTDchildren = [[v] for v in range(nVTDs)]  #the list of all fragment numbers associated with the original VTD, including ones that get surrounded\n",
    "countyFragVTDset = [set(countyTractList[c]) for c in range(nCounties)]\n",
    "for v in populatedTractList:\n",
    "    c = countyNo[v]\n",
    "    if c not in allFusedCounties and c not in unitCounties: \n",
    "        if vtdGeom[v].geom_type != dummyPoly.geom_type :  #a multipoly vtd-based unit\n",
    "            nFragmentedVTDs +=1\n",
    "            fragmentedVTDs.append(v)\n",
    "            geos, areas = [geo for geo in vtdGeom[v].geoms ], [geo.area for geo in vtdGeom[v].geoms]\n",
    "            for i, geo in enumerate(geos):\n",
    "                if i == 0:\n",
    "                    fragVTDgeom[v] = geo\n",
    "                    fragVTDpop[v] = tractPop[v] * areas[i] / np.sum(areas)  #overwrite, then distribute balance below\n",
    "                else:\n",
    "                    fNo = len(fragVTDgeom)\n",
    "                    fragVTDgeom.append(geo)\n",
    "                    fragVTDpop.append( tractPop[v] * areas[i] / np.sum(areas) )\n",
    "                    parentVTDno.append(v)\n",
    "                    countyFragVTDset[c].add(fNo )\n",
    "                    VTDchildren[v].append(fNo)\n",
    "                    nVTDneighbors.append(0)\n",
    "                    lastVTDneighbor.append(-999)\n",
    "                    \n",
    "print(\"I split up\",nFragmentedVTDs,\"fragmented VTDs. Now define unit neighbor lists and fuse geometries of surrounds.\")\n",
    "\n",
    "debugV = -7616\n",
    "for kk,V in enumerate(populatedTractList):\n",
    "    if kk%500 == 0:\n",
    "        print(\"looking for surrounds, now working on vtd\",V)\n",
    "    c = countyNo[V]\n",
    "    if c not in allFusedCounties and c not in unitCounties:\n",
    "        for v in VTDchildren[V]:\n",
    "            for vv in countyFragVTDset[c].difference({v}) :\n",
    "                if fragVTDgeom[vv].intersects(fragVTDgeom[v]):\n",
    "                    nVTDneighbors[v] +=1\n",
    "                    lastVTDneighbor[v] = vv\n",
    "                    if v == debugV:\n",
    "                        print(\"I just added neighbor\",vv,\"to magicV\",v)\n",
    "                #if nVTDneighbors[v] >= 4:  #Enough to have >=2 even after surrounds.  Will do full neighbor list later\n",
    "                #    break\n",
    "            if nVTDneighbors[v] < 4:  #OK if a vtd has only 1 intracounty neighbor IF it touches another county, it's not surrounded\n",
    "                for cc in neighborCountyList[c]:\n",
    "                    if fragVTDgeom[v].intersects(countyGeom[cc]):\n",
    "                        if cc not in unitCounties + allFusedCounties:\n",
    "                            for vv in countyFragVTDset[cc] :\n",
    "                                if fragVTDgeom[vv].intersects(fragVTDgeom[v]):\n",
    "                                    nVTDneighbors[v] +=1\n",
    "                                    lastVTDneighbor[v] = vv\n",
    "                            if nVTDneighbors[v] == 1:\n",
    "                                print(\"WARNING. vtd frag\",v,\"in county\",c,\"intersected county\",cc,\"but had no intracounty neighbors\")\n",
    "                                plotPoly(fragVTDgeom[v],2)\n",
    "                                plotCenter(\"iso\",fragVTDgeom[v])\n",
    "                                plotPoly(countyGeom[cc])\n",
    "                        else:\n",
    "                            nVTDneighbors[v] +=1\n",
    "                            if nVTDneighbors[v] == 1:\n",
    "                                raise Exception(\"neighborless vtd fragment\",v,\"neighbors a unit or fused county\",cc)                                \n",
    "            if v == debugV:\n",
    "                print(v,\"has\",nVTDneighbors[v],\"neighbors.  its last is\",lastVTDneighbor[v])\n",
    "                \n",
    "for loop in range(3): #to catch surrounds of surrounds\n",
    "    for V in populatedTractList:\n",
    "        c = countyNo[V]\n",
    "        if c not in allFusedCounties and c not in unitCounties: \n",
    "            for v in VTDchildren[V]:\n",
    "                if nVTDneighbors[v] == 1:\n",
    "                    vv = lastVTDneighbor[v]\n",
    "                    if v in surrounders:  #transferring surrounded of surrounds to master surrounder\n",
    "                        for sNo, s in enumerate(surroundedVTDs):\n",
    "                            if surrounders[sNo] == v:\n",
    "                                surrounders[sNo] = vv\n",
    "                    surroundedVTDs.append(v)\n",
    "                    surrounders.append(vv)\n",
    "                    nVTDneighbors[vv] -=1\n",
    "                    nVTDneighbors[v] -=1 #in case this surrounder becomes a later surroundee\n",
    "                    fragVTDpop[vv] += fragVTDpop[v]\n",
    "                    fragVTDpop[v] = 0\n",
    "                    if lastVTDneighbor[vv] == v:  #find another neighbor in case this surrounder is also a surroundee in loop 2\n",
    "                        for vvv in countyFragVTDset[c]:\n",
    "                            if vvv not in [v,vv]:\n",
    "                                if fragVTDgeom[vvv].intersects(fragVTDgeom[vv]):\n",
    "                                    lastVTDneighbor[vv] = vvv\n",
    "                    if lastVTDneighbor[vv] == v:\n",
    "                        print(\"WARNING.  We did not find another neighbor of surrounder\",vv,\"other than surroundee\",v)\n",
    "                    if loop > 0:\n",
    "                        print(\"On loop\",loop+1,\"for county\",c,\" we found that vtd frag\",v,\"now has only 1 neighbor\",vv)\n",
    "if STATE == \"NJ\":  #state-specific manual surround enforcement\n",
    "    c = 18\n",
    "    print(\"visualizing VTD fragments in county\",c)\n",
    "    for v in countyFragVTDset[c]:\n",
    "        plotPoly(fragVTDgeom[v])\n",
    "        plotCenter(v, fragVTDgeom[v])\n",
    "    plt.show()\n",
    "    specialSurrounded = ast.literal_eval(input(\"enter the [v1, v2, ...] list of surrounded fragVTDs from above map\"))\n",
    "    specialSurrounder = int(input(\"enter the fragVTDno that surrounds these\"))\n",
    "    #specialSurrounded = [1713, 1718]\n",
    "    #specialSurrounder = 1712\n",
    "    print(\"special for\",STATE,\", I believe that\", specialSurrounded,\"are surrounded by vtd (fragment)\",specialSurrounder,\". Here, let me show you\")\n",
    "    c = countyNo[parentVTDno[specialSurrounder]]\n",
    "    plotPoly(countyGeom[c], 0.5)\n",
    "    for v in specialSurrounded:\n",
    "        plotPoly(fragVTDgeom[v])\n",
    "        plotCenter(v,fragVTDgeom[v])\n",
    "    plotPoly(fragVTDgeom[specialSurrounder],0.2)\n",
    "    plotCenter(specialSurrounder, fragVTDgeom[specialSurrounder], 8)\n",
    "    plt.show()\n",
    "    shouldIcombine = int(input(\"enter 1 to apply the surrounding operation\"))\n",
    "    if shouldIcombine == 1:\n",
    "        for v in specialSurrounded:\n",
    "            vv = specialSurrounder\n",
    "            if v in surrounders:  #transferring surrounded of surrounds to master surrounder\n",
    "                for sNo, s in enumerate(surroundedVTDs):\n",
    "                    if surrounders[sNo] == v:\n",
    "                        surrounders[sNo] = vv\n",
    "            surroundedVTDs.append(v)\n",
    "            surrounders.append(vv)\n",
    "            nVTDneighbors[vv] -=1\n",
    "            nVTDneighbors[v] = 0 #we are capturing all surroundees (some of whom may touch other surroundees)\n",
    "            fragVTDpop[vv] += fragVTDpop[v]\n",
    "            fragVTDpop[v] = 0\n",
    "\n",
    "\n",
    "for V in populatedTractList:\n",
    "    c = countyNo[V]\n",
    "    if c not in allFusedCounties and c not in unitCounties: \n",
    "        for v in VTDchildren[V]:\n",
    "            if nVTDneighbors[v] >1:\n",
    "                unitCP.append(fragVTDgeom[v].centroid)\n",
    "                unitGeom.append(fragVTDgeom[v])\n",
    "                unitPop.append(fragVTDpop[v])   #for now, ratio pop by area, not block decomposition\n",
    "                vtdUnits.append(v)   #if a border unit, we'll catch in below big loop, after checking for surround\n",
    "                allUnits.append(v)\n",
    "#for V in populatedTractList:\n",
    "#    c = countyNo[V]\n",
    "#    if c not in allFusedCounties and c not in unitCounties:  \n",
    "#        for v in VTDchildren[V]: \n",
    "for V in populatedTractList:\n",
    "    c = countyNo[V]\n",
    "    if c not in allFusedCounties and c not in unitCounties: \n",
    "        for v in VTDchildren[V]:\n",
    "            if nVTDneighbors[v] == 1:  #a surrounded VTD, transfer its pop to surrounder unit.  Don't bother with shifting centerpoints\n",
    "                print(\"somehow we missed 1-neighbor vtd frag\",v,\" with last vtd frag nbr\",lastVTDneighbor[v])\n",
    "            if nVTDneighbors[v] == 0 and v not in surroundedVTDs:\n",
    "                print(\"WARNING. unsurrounded vtd\",v,\"had no found neighbors\")\n",
    "\n",
    "for i, L in enumerate(CCBlist):\n",
    "    unitCP.append( CCBcp[i] )\n",
    "    unitPop.append(CCBpop[i])\n",
    "    unitGeom.append(   CCBgeom[i])\n",
    "    nbrUnitGeom.append(CCBgeom[i])\n",
    "    allUnits.append(i+0.25)  #use alt non-integers to avoid vtd and county and cluster confusion\n",
    "\n",
    "nUnits = len(allUnits)\n",
    "print(\"After surround checks, we appear to have\",nUnits,\"building blocks defined. We captured\",len(surroundedVTDs),\"surrounded VTDs\")\n",
    "\n",
    "unitNbrs = [list() for u in range(nUnits)]\n",
    "countyUnitList = [list() for c in range(nCounties)]\n",
    "for c in uncutCountyList:\n",
    "    for v in countyFragVTDset[c]:\n",
    "        if v in allUnits:\n",
    "            countyUnitList[c].append(allUnits.index(v))\n",
    "\n",
    "sketchyList = list()\n",
    "for c in uncutCountyList:\n",
    "    if c%20 == 0:\n",
    "        print(\"working on unit neighbor lists for county\",c)\n",
    "    if c not in allFusedCounties:  #see a separate loop below for cluster-cluster neighbors\n",
    "        if c in unitCounties:    \n",
    "            u = allUnits.index(c+0.5)\n",
    "            for cc in neighborCountyList[c]:\n",
    "                if cc not in allFusedCounties:\n",
    "                    if cc in unitCounties:\n",
    "                        unitNbrs[u].append(allUnits.index(cc+0.5))  #we'll catch the complement in the cc county's loop\n",
    "                    else:\n",
    "                        for uu in countyUnitList[cc] :\n",
    "                            if countyGeom[c].intersects(unitGeom[uu]):\n",
    "                                unitNbrs[u].append(uu)\n",
    "                                unitNbrs[uu].append(u)\n",
    "            for i,geo in enumerate(CCBgeom):\n",
    "                if geo.intersects(countyGeom[c]):\n",
    "                    unitNbrs[u].append(allUnits.index(i+0.25) )\n",
    "                    unitNbrs[allUnits.index(i+0.25) ].append(u)\n",
    "        else:  #non-unit county      \n",
    "            for u in countyUnitList[c] :\n",
    "                for uu in list( set(countyUnitList[c]).difference({u}) ) :\n",
    "                    if unitGeom[u].intersects(unitGeom[uu]):\n",
    "                        unitNbrs[u].append(uu )  #will catch complement later in this county's loop\n",
    "                for cc in neighborCountyList[c]:\n",
    "                    if cc not in allFusedCounties and cc not in unitCounties: #see an above block for handling unitCounties\n",
    "                        for uu in countyUnitList[cc]:\n",
    "                            if unitGeom[u].intersects(unitGeom[uu]):\n",
    "                                unitNbrs[u].append(uu )\n",
    "\n",
    "            for u in countyUnitList[c] :\n",
    "                for i,geo in enumerate(CCBgeom):\n",
    "                    if geo.intersects(unitGeom[u]):\n",
    "                        unitNbrs[u].append(allUnits.index(i+0.25) )\n",
    "                        unitNbrs[allUnits.index(i+0.25) ].append(u)\n",
    "                if len(unitNbrs[u]) == 0:\n",
    "                    print(\"ERROR - unit\",u,\" = vtd\",allUnits[u],\"in county\", c,\"has no neighbors\")\n",
    "                if len(unitNbrs[u]) == 1:  #after fragmentation, this unit appears surrounded.  Next block to confirm it has non-intracounty neighbors                       \n",
    "                    print(\"WARNING - unit\",u,\" = vtd\",allUnits[u],\"in county\", c,\"has only 1 neighbor=\",unitNbrs[u],\". Optional triage in next block\")\n",
    "                    sketchyList.append([u,unitNbrs[u][0] ] )\n",
    "\n",
    "CCBunits = CCBlist.copy()                        \n",
    "for i, geo in enumerate(CCBgeom):  #this loop: only cluster-cluster intersections.  Cluster-vtd and cluster-county neighbors already found above.\n",
    "    for ii in range(i+1,len(CCBgeom) ) :\n",
    "        if geo.intersects(CCBgeom[ii]):\n",
    "            unitNbrs[allUnits.index(i+0.25) ].append(allUnits.index(ii+0.25) ) #all CCB-county, CCB-vtd intersxns already covered\n",
    "            unitNbrs[allUnits.index(ii+0.25)].append(allUnits.index(i+0.25) )\n",
    "print(\"All done creating unit lists\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "94741893-6835-45ac-9793-64cbaf4823b2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sketchy unit 1173 has neighbor list [1673, 2]\n"
     ]
    }
   ],
   "source": [
    "for L in sketchyList:  #hope that some of these flagged units picked up unit-county or CCB neighbors\n",
    "    print(\"sketchy unit\",L[0], \"has neighbor list\",unitNbrs[L[0]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "cb4277b4-d6ef-4c8c-aa23-6fde227379ff",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for u in range(nUnits):\n",
    "    if allUnits[u] - int(allUnits[u]) == 0.25:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(u,unitGeom[u])\n",
    "plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "e79873ab-0b8e-48a9-b4b0-05b3135b9cc3",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "8378940d-4387-4188-8ae1-a62010500ecb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now build the border topology\n",
      "counties and clusters done, now working on (frag) vtd-based units\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Now build the border topology\")\n",
    "borderUnits, borderType = list(), list()\n",
    "for c in borderCounties:\n",
    "    if c in unitCounties:\n",
    "        borderUnits.append(allUnits.index(c+0.5))\n",
    "        borderType.append(\"county\")\n",
    "for i,L in enumerate(CCBlist):\n",
    "    if CCBgeom[i].intersects(MAPexterior):  #should always be the case\n",
    "        borderUnits.append(allUnits.index(i+0.25))\n",
    "        borderType.append(\"cluster\")\n",
    "print(\"counties and clusters done, now working on (frag) vtd-based units\")\n",
    "for c in borderCounties:\n",
    "    if c not in unitCounties + allFusedCounties:\n",
    "        for u in countyUnitList[c]:\n",
    "            if unitGeom[u].intersects(MAPexterior):\n",
    "                borderUnits.append(u)\n",
    "                borderType.append(\"vtd\")                \n",
    "    \n",
    "for i,b in enumerate(borderUnits):\n",
    "    plotPoly(unitGeom[b])\n",
    "    if borderType[i] == \"cluster\":\n",
    "        j = int(allUnits[b])\n",
    "        for c in CCBlist[j]:\n",
    "            plotPoly(countyGeom[c],0.2)\n",
    "            plotCenter(\"fused\",countyGeom[c], 6)\n",
    "for c in unitCounties:\n",
    "    plotPoly(countyGeom[c],0.4)\n",
    "    plotCenter(\"unit\",countyGeom[c],8)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "937d923d-9e95-45e9-9aef-77cb4377781d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking that the list of borderUnits is contiguous all around\n",
      "number of border units = 268\n"
     ]
    }
   ],
   "source": [
    "print(\"checking that the list of borderUnits is contiguous all around\")\n",
    "print(\"number of border units =\",len(borderUnits))\n",
    "for u in borderUnits:\n",
    "    isUnbroken, smallPieceList = isContiguous(list(set(borderUnits).difference({u})),unitNbrs)\n",
    "    if not isUnbroken:\n",
    "        print(\"border is discontig if we skip\",u)\n",
    "        for uu in smallPieceList:\n",
    "            plotPoly(unitGeom[uu],0.5)\n",
    "            plotCenter(\"n\"+str(uu),unitGeom[uu])\n",
    "        plotCenter(u,unitGeom[u])\n",
    "        plotPoly(unitGeom[u])\n",
    "        plt.show()\n",
    "borderSet = set(borderUnits)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "93603f77-77fa-4453-b54b-5ea07fcb6721",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here, we identify 'border' units that aren't needed to define the map border\n",
      "Bueno! no 'border units' that could be eliminated from the border set\n"
     ]
    }
   ],
   "source": [
    "print(\"here, we identify 'border' units that aren't needed to define the map border\")\n",
    "canBeRemoved, powerNeighbors = set(), set()\n",
    "for u in borderUnits:\n",
    "    uNeighbors = list(borderSet.intersection(set(unitNbrs[u])) )\n",
    "    if len(uNeighbors) < 2:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(u,unitGeom[u])\n",
    "        uu = uNeighbors[0]\n",
    "        otherBorderNeighbors = set(unitNbrs[uu]).intersection(borderSet).difference({u})\n",
    "        if len(otherBorderNeighbors) > 1:  #this neighbor of our 1-border-neighbor border unit makes a border chain without the problem border unit\n",
    "            canBeRemoved.add(u)\n",
    "            powerNeighbors.add(uu)\n",
    "        plotCenter(uu,unitGeom[uu],6)\n",
    "        plotPoly(unitGeom[uu],0.5)\n",
    "        for uuu in set(unitNbrs[uu]).intersection(borderSet).difference({u}):\n",
    "            plotPoly(unitGeom[uuu])\n",
    "            plotCenter(str(uuu)+\"=N of\"+str(uu),unitGeom[uuu])\n",
    "        for uuu in set(unitNbrs[u]).difference(borderSet):\n",
    "                plotCenter(uuu+0.1,unitGeom[uuu],6)\n",
    "                plotPoly(unitGeom[uuu],0.1)\n",
    "        c = countyNo[allUnits[u]]\n",
    "        #plotPoly(countyGeom[c] )\n",
    "        #plotCenter(c, countyGeom[c])\n",
    "        plt.show()\n",
    "if len(canBeRemoved) == 0:\n",
    "    print(\"Bueno! no 'border units' that could be eliminated from the border set\")\n",
    "else:\n",
    "    print(canBeRemoved,\"is the list of 1-neighbor 'border' units that can be eliminated from the border set\")\n",
    "    print(\"... as they are enveloped on the border; the enveloping border unit has two other map-border neighbors\")\n",
    "    yesRemove = input(\"enter 1 to remove these from the list of border units\")\n",
    "    if int(yesRemove) == 1:\n",
    "        canRemove = True\n",
    "        for uu in powerNeighbors:\n",
    "            testSet = (borderSet.difference(canBeRemoved)).difference({uu})\n",
    "            if not isContiguous(list(testSet),unitNbrs):\n",
    "                canRemove = False\n",
    "                print(\"We can't complete the border if unit\",uu,\"is not included in the ring\")\n",
    "        if canRemove:\n",
    "            borderSet = borderSet.difference(canBeRemoved)\n",
    "            borderList = list(borderSet)\n",
    "            borderUnits = list(borderSet)\n",
    "            print(\"Success! we removed\",canBeRemoved,\"from the list of borderUnits\")\n",
    "    else:\n",
    "        print(\"Fine, be that way.  Sheesh, I will keep them.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "b13c68e3-33ed-48b3-acca-78012ce0bf61",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here is the final border set\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for u in borderUnits:\n",
    "    plotPoly(unitGeom[u])\n",
    "print(\"here is the final border set\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "173bb175-312b-4d08-a5b5-80a1d5d70416",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n"
     ]
    }
   ],
   "source": [
    "print(isContiguous(borderUnits,unitNbrs)[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "fc1ae6e1-ef52-412b-a966-e9739071af8f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For safekeeping, write the unit topology to a file\n"
     ]
    }
   ],
   "source": [
    "date_ = \"20Apr24\"\n",
    "print(\"For safekeeping, write the unit topology to a file\")  \n",
    "unitParentVTDno = [-999 for u in range(nUnits)]\n",
    "for u in range(nUnits):    \n",
    "    if allUnits[u] %1 == 0:\n",
    "        v = allUnits[u]\n",
    "        unitParentVTDno[u] = parentVTDno[v]\n",
    "\n",
    "unitVTDlist = [list() for u in range(nUnits)]\n",
    "for u in range(nUnits):\n",
    "    if allUnits[u] % 1 == 0.5 :\n",
    "        c = int(allUnits[u])\n",
    "        unitVTDlist[u] = countyTractList[c].copy()\n",
    "    if allUnits[u] % 1 == 0.25 :\n",
    "        CCBnumber = int(allUnits[u])\n",
    "        for c in CCBlist[CCBnumber] :\n",
    "            unitVTDlist[u] += countyTractList[c]\n",
    "    if allUnits[u] % 1 == 0:\n",
    "        unitVTDlist[u] = [allUnits[u]]\n",
    "        #for i,uu in enumerate(surrounders):  #no longer tracked\n",
    "         #   if u == uu:\n",
    "         #       unitVTDlist[u].append(surroundedVTDs[i])\n",
    "                \n",
    "unitNo = [u for u in range(nUnits)]\n",
    "unitCPx, unitCPy = [unitCP[u].x for u in range(nUnits)], [unitCP[u].y for u in range(nUnits)]\n",
    "onBorder = [0 for u in range(nUnits)]\n",
    "for u in borderUnits:\n",
    "    onBorder[u] = 1\n",
    "nbrDF = pd.DataFrame( {\"unitNo\":unitNo,\"centroid x\":unitCPx,\"centroid y\":unitCPy,\"unitPop\":unitPop,\"onBorder\":onBorder,\n",
    "                       \"neighborList\":unitNbrs, \"unitVTDlist\":unitVTDlist, \"unitParentVTDno\": unitParentVTDno, \"allUnits\":allUnits} )\n",
    "outname = STATE+\"unitTopologies_\"+date_+\".csv\" \n",
    "outpath = \"state_map_files/\"+outname\n",
    "nbrDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "d4baaea4-7af4-4407-aeb3-f4291d335f89",
   "metadata": {},
   "outputs": [],
   "source": [
    "vtdGeom = tractGeom.copy()  #optional reset if we need to rerun the below clipPoly routine with alternate clipPolys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "abdd07e7-f9be-480a-9d3d-b3948eeaaa2e",
   "metadata": {},
   "outputs": [],
   "source": [
    "toSquishCountiesList = list()   #default; if we did not have any clipPoly's to move in\n",
    "nClips = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "4d5fdc3c-6126-4fa8-b484-1d0052c70aed",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "for some states like FL, MD, MN, NC we move in partial counties via clipPoly's before running option 2\n",
      "adding code here to 'push in' state panhandles ...\n",
      "performing squish no 1 for state NJ\n",
      "clipPoly 0 intersects [4] counties and a total of 85 units\n",
      "Here is the original cutLine and an alternate based on cut shapes\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "These are your orig (faint) and squished shapes for clip no 1 out of 1\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 when ready 1\n"
     ]
    }
   ],
   "source": [
    "#starting with MN, we moved the \"option2\" block earlier in the notebook, as we run it before running option 1 (as in other states)\n",
    "print(\"for some states like FL, MD, MN, NC we move in partial counties via clipPoly's before running option 2\")\n",
    "vtdCP = tractCP.copy()\n",
    "#CODE TO SQUISH GEOMETRIES FROM CLIP LINES INTO THE MAP\n",
    "print(\"adding code here to 'push in' state panhandles ...\")\n",
    "trimDF = pd.read_csv(\"state_map_files/cutNclipPolyLists.csv\")\n",
    "stateRows = trimDF[\"state\"].to_list()\n",
    "DFrow = stateRows.index(STATE)\n",
    "nClips = trimDF[\"nClipPoly\"][DFrow]\n",
    "nCuts  = trimDF[\"nCutPoly\"][DFrow]\n",
    "#Adding in here trimming ops\n",
    "toSquishUnitsList = list()\n",
    "toSquishGeomsList = list()  #combined list of geoms we will squish (over all squish operations)\n",
    "toSquishCountiesList = list()\n",
    "squishedShapesList = list()   #unit shapes after squishing, list over all squish operations\n",
    "if nClips > 0:\n",
    "    clipPoints = ast.literal_eval(trimDF[\"clipPoints\"][DFrow])   #sets of four points\n",
    "    farPoints  = ast.literal_eval(trimDF[\"farPoints\"][DFrow])    #pairs of points\n",
    "    newFarPoints  = ast.literal_eval(trimDF[\"newFarPoints\"][DFrow])   #pairs\n",
    "    cPts = [Point(clipPoints[i][0],clipPoints[i][1]) for i in range(len(clipPoints)) ]\n",
    "    fPts = [Point(farPoints[i][0],farPoints[i][1]) for i in range(len(farPoints)) ]\n",
    "    nfPts = [Point(newFarPoints[i][0],newFarPoints[i][1]) for i in range(len(newFarPoints)) ]\n",
    "    \n",
    "    for clipNo in range(nClips):\n",
    "        print(\"performing squish no\",clipNo+1,\"for state\",STATE)\n",
    "        n0,n1,n2,n3 = int(4*clipNo), int(4*clipNo+1), int(4*clipNo+2), int(4*clipNo+3)\n",
    "        clipPoly = Polygon([cPts[n0],cPts[n1],cPts[n2],cPts[n3] ] )\n",
    "        cutLine = LineString([cPts[n0],cPts[n1]] )\n",
    "        farLine = LineString([fPts[int(2*clipNo)],fPts[int(2*clipNo+1)] ] )\n",
    "        newFarLine = LineString([nfPts[int(2*clipNo)],nfPts[int(2*clipNo+1)] ])\n",
    "        \n",
    "        toSquishCounties = list()\n",
    "        toSquishUnits = list()\n",
    "        for c in range(nCounties):\n",
    "            if clipPoly.intersects(countyGeom[c]):\n",
    "                toSquishCounties.append(c)\n",
    "                if clipPoly.contains(countyGeom[c]):\n",
    "                    toSquishUnits = toSquishUnits + countyTractList[c]\n",
    "                else:\n",
    "                    for t in countyTractList[c]:\n",
    "                        if clipPoly.contains(vtdCP[t]):\n",
    "                            toSquishUnits.append(t)\n",
    "        print(\"clipPoly\",clipNo,\"intersects\",toSquishCounties,\"counties and a total of\",len(toSquishUnits),\"units\")\n",
    "        toSquishGeomUnion = vtdGeom[toSquishUnits[0]]\n",
    "        toSquishGeoms = list()\n",
    "        for t in toSquishUnits:\n",
    "            toSquishGeomUnion = toSquishGeomUnion.union(vtdGeom[t])\n",
    "            toSquishGeoms.append(vtdGeom[t])\n",
    "        unclippedGeom = MAP.difference(toSquishGeomUnion)\n",
    "        altCutLine = toSquishGeomUnion.buffer(0.001).intersection(unclippedGeom)\n",
    "        print(\"Here is the original cutLine and an alternate based on cut shapes\")\n",
    "        #plotPoly(MAP,0.1)\n",
    "        plotPoly(cutLine.buffer(0.02))\n",
    "        plotPoly(altCutLine,0.1)\n",
    "        plt.show()\n",
    "        # could use altCutLine for a more accurate squish at the squish-no_squish boundary ...\n",
    "        #newShapes = squish(clippedGeomList, altCutLine, farLine, newFarLine)\n",
    "        squishedShapes = squish(toSquishGeoms, cutLine, farLine, newFarLine) #..but may distort results\n",
    "        toSquishUnitsList.append(toSquishUnits)\n",
    "        toSquishGeomsList.append(toSquishGeoms)\n",
    "        toSquishCountiesList.append(toSquishCounties)\n",
    "        squishedShapesList.append(squishedShapes)\n",
    "        for geo in toSquishGeoms:\n",
    "            plotPoly(geo,0.1)\n",
    "            plotPoly(geo.centroid.buffer(0.004),0.1)\n",
    "        for geo in squishedShapes:\n",
    "            plotPoly(geo)\n",
    "            plotPoly(geo.centroid.buffer(0.002),0.4)\n",
    "        print(\"These are your orig (faint) and squished shapes for clip no\",clipNo+1,\"out of\",nClips)\n",
    "        plt.show()\n",
    "        pause = input(\"enter 1 when ready\")    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "62667c48-6c66-4381-b01d-518af61651bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "#now apply the squish to all impacted vtds.  \"tractGeom\" will retain original vtd shapes, so we can reset if needed\n",
    "for i, vList in enumerate(toSquishUnitsList):\n",
    "    squishedShapes = squishedShapesList[i]\n",
    "    for j, v in enumerate(vList):\n",
    "        vtdGeom[v] = squishedShapes[j]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "7b967d22-41fb-454f-ae47-d72d712daa4c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for t in range(nTracts):  #optional full state visualization after squish\n",
    "    if t not in allCutVTDs and t not in skipList:\n",
    "        plotPoly(vtdGeom[t])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9715564f-3b60-43e5-9f1f-02f3dcee3933",
   "metadata": {},
   "outputs": [],
   "source": [
    "c = 22  #pick a county for visualization if desired\n",
    "print(\"here are the faint(original) and squished shapes for county\",c)\n",
    "for t in countyTractList[c]:\n",
    "    plotPoly(vtdGeom[t])\n",
    "    plotPoly(tractGeom[t],0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "760bc48e-0236-4ad7-b3b8-d74795009f53",
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"alternate simple approach for Florida Keys - translate all toward county CP\")\n",
    "c = 43\n",
    "vtdGeom = tractGeom.copy()  #a reset\n",
    "nTranslated = 0\n",
    "newCP = Point(-81, 25.1)\n",
    "for v in countyTractList[c]:\n",
    "    if clipPoly.contains(tractCP[v]):\n",
    "        xDelta, yDelta = newCP.x - tractCP[v].x, newCP.y - tractCP[v].y\n",
    "        xOFF, yOFF = 0.95 * xDelta, 0.95 * yDelta\n",
    "        vtdGeom[v] = translate(vtdGeom[v],xoff= xOFF, yoff=yOFF)\n",
    "        nTranslated +=1\n",
    "print(\"I translated\",nTranslated,\"vtds toward the center of county\",c)\n",
    "hdCP = [vtdGeom[v].centroid for v in range(nTracts)]\n",
    "countyGeom[c] = vtdGeom[countyTractList[c][0]]\n",
    "for v in countyTractList[c]:\n",
    "    countyGeom[c] = countyGeom[c].union(vtdGeom[v])\n",
    "    plotPoly(hdCP[v].buffer(0.03))\n",
    "plotPoly(countyGeom[c])\n",
    "unsquishedMAP = MAP\n",
    "MAP = countyGeom[uncutCountyList[0]]\n",
    "for c in uncutCountyList:\n",
    "    MAP = MAP.union(countyGeom[c])\n",
    "#plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "4ef91f8f-dabb-4c58-a8a4-bba8e725e586",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here we compute the map's convex hull. We can build out of whole counties or after squish operations.\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 to use shifted shapes (e.g. for MD, MN), else enter 0 for most states to use uncut counties 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on confirming HD center 0 is inside the map's convex hull\n",
      "working on confirming HD center 500 is inside the map's convex hull\n",
      "working on confirming HD center 1000 is inside the map's convex hull\n",
      "working on confirming HD center 1501 is inside the map's convex hull\n",
      "working on confirming HD center 2002 is inside the map's convex hull\n",
      "working on confirming HD center 2503 is inside the map's convex hull\n",
      "working on confirming HD center 3003 is inside the map's convex hull\n",
      "working on confirming HD center 3503 is inside the map's convex hull\n",
      "working on confirming HD center 4003 is inside the map's convex hull\n",
      "working on confirming HD center 4503 is inside the map's convex hull\n",
      "working on confirming HD center 5003 is inside the map's convex hull\n",
      "working on confirming HD center 5504 is inside the map's convex hull\n",
      "working on confirming HD center 6004 is inside the map's convex hull\n",
      "Here is the convex hull and shape and a dot map of the (shifted) unit centerpoints\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Note the MAP convex hull.  Overwrite with your own polygon if desired.\n"
     ]
    }
   ],
   "source": [
    "#OPTION 2 - draw polygonal HDs.  #REQUIRES CONSISTENT TREATMENT OF CCB'S \n",
    "#For GA, MA, MD, MN, NC we draw HDs for ALL vtds, even if they are in a CCB.  We use the clipPoly's to squish in the corners for these HD shapes\n",
    "#Not sure if below would work if we have cut districts AND squished-in corners\n",
    "#We normally draw for each (squished or orig) vtd.  Or, read in tract or blockgroup geometries, use those pops and unit centerpoints\n",
    "\n",
    "hdCP = [vtdGeom[v].centroid for v in range(nTracts)]  #remember, this is after any squish operation\n",
    "print(\"Here we compute the map's convex hull. We can build out of whole counties or after squish operations.\")\n",
    "useSquish = int(input(\"enter 1 to use shifted shapes (e.g. for MD, MN), else enter 0 for most states to use uncut counties\"))\n",
    "if useSquish == 1:\n",
    "    convexMAP = hdCP[countyTractList[uncutCountyList[0]][0]].buffer(0.1) \n",
    "    for v in range(nTracts):\n",
    "        if v not in skipList and v not in allCutVTDs:\n",
    "            convexMAP = convexMAP.union(hdCP[v].buffer(0.1))\n",
    "else:  #build the map via simple union of counties not wholly in fully cut-out districts\n",
    "    convexMAP = countyGeom[uncutCountyList[0]]\n",
    "    for c in uncutCountyList:\n",
    "        convexMAP = convexMAP.union(countyGeom[c])\n",
    "    #convexMAP = MAP.centroid\n",
    "    #for c in range(nCounties):\n",
    "    #    if c not in allFusedCounties:\n",
    "    #        convexMAP = convexMAP.union(countyGeom[c])\n",
    "MAPhull = convexMAP.convex_hull.buffer(0.01*convexMAP.area**0.5)\n",
    "plotPoly(MAPhull)\n",
    "popHDlist = list()\n",
    "for t in range(nTracts):\n",
    "    if t not in allCutVTDs and t not in skipList:  #keep low-pop tracts as VEST may have assigned voters to them\n",
    "        popHDlist.append(t)\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%500 == 0:\n",
    "        print(\"working on confirming HD center\",t,\"is inside the map's convex hull\")\n",
    "    if hdCP[t].disjoint(convexMAP.convex_hull):\n",
    "        plotPoly(hdCP[t].buffer(0.03))\n",
    "        hdCP[t] = nearest_points(convexMAP.convex_hull,hdCP[t])[0]\n",
    "        plotCenter(\"m\",hdCP[t])\n",
    "    else:\n",
    "        plotPoly(hdCP[t].buffer(0.01))\n",
    "plotPoly(convexMAP)\n",
    "plotPoly(convexMAP.convex_hull)\n",
    "plotPoly(MAPhull)\n",
    "for c in allFusedCounties:\n",
    "    plotPoly(countyGeom[c],0.2)\n",
    "print(\"Here is the convex hull and shape and a dot map of the (shifted) unit centerpoints\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Note the MAP convex hull.  Overwrite with your own polygon if desired.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "8393e96a-75c6-48ec-94e8-1f6fe58d31df",
   "metadata": {},
   "outputs": [],
   "source": [
    "nHDs = nTracts  #need to run this if we start option 2 from a vest list, not a previously run HD poly list\n",
    "HDcountyNo = countyNo.copy()\n",
    "populatedTractList = popHDlist.copy()  #nomenclature equivalency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "bcaf6ea2-1c3b-48c1-9ad6-937d7b7e4385",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Let us establish the (post-squish) point-point distances for all HD centers, about 8 min for 4000-unit state\n",
      "working on tract-tract distances for unit 0 out of 6361 . Time = 0\n",
      "working on tract-tract distances for unit 400 out of 6361 . Time = 139\n",
      "working on tract-tract distances for unit 800 out of 6361 . Time = 260\n",
      "working on tract-tract distances for unit 1200 out of 6361 . Time = 366\n",
      "working on tract-tract distances for unit 1601 out of 6361 . Time = 468\n",
      "working on tract-tract distances for unit 2002 out of 6361 . Time = 548\n",
      "working on tract-tract distances for unit 2403 out of 6361 . Time = 632\n",
      "working on tract-tract distances for unit 2803 out of 6361 . Time = 706\n",
      "working on tract-tract distances for unit 3203 out of 6361 . Time = 774\n",
      "working on tract-tract distances for unit 3603 out of 6361 . Time = 830\n",
      "working on tract-tract distances for unit 4003 out of 6361 . Time = 881\n",
      "working on tract-tract distances for unit 4403 out of 6361 . Time = 924\n",
      "working on tract-tract distances for unit 4803 out of 6361 . Time = 959\n",
      "working on tract-tract distances for unit 5203 out of 6361 . Time = 986\n",
      "working on tract-tract distances for unit 5604 out of 6361 . Time = 1005\n",
      "working on tract-tract distances for unit 6004 out of 6361 . Time = 1016\n",
      "All done; total elapsed  1019 seconds for NJ with 12 districts to map\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "our maxD was 1.5\n"
     ]
    }
   ],
   "source": [
    "#continuing option 2 ....... ##########  THIS IS FOR TRACT - TRACT, despite the \"unit\" nomenclature\n",
    "print(\"Let us establish the (post-squish) point-point distances for all HD centers, about 8 min for 4000-unit state\")\n",
    "#NOTE: FOR LARGE STATES, RESTRICT THE SEARCH TO COUNTIES WITHIN A 3/SQRT(nDistrict) DIAMETER OF THE HOME UNIT\n",
    "uuDist = [[int(maxD+1) for t in range(nHDs)] for t in range(nHDs)] #default: too big to capture\n",
    "closeCountyList = [list() for c in range(nCounties)]\n",
    "closeCountyDist = maxD   #min(maxD,3./float(nDistricts)**0.5 * maxD )  #use above maxD for these counties as well\n",
    "xScaleSquared = xScale*xScale\n",
    "if nDistricts < 10: #closeCountyDist >= maxD:  #small state\n",
    "    closeCountyList = [[i for i in range(nCounties)] for c in range(nCounties)]  #all counties are close enough\n",
    "else:\n",
    "    for c in uncutCountyList:\n",
    "        closeCountyList[c].append(c)\n",
    "        for cc in range(c+1,nCounties):\n",
    "            if cc in uncutCountyList:\n",
    "                if cc in neighborCountyList[c]:\n",
    "                    closeCountyList[c].append(cc)\n",
    "                    closeCountyList[cc].append(c)\n",
    "                else:    \n",
    "                    dist = getLongDist(countyCP[c], countyCP[cc],xScale)\n",
    "                    if dist < closeCountyDist:\n",
    "                        closeCountyList[c].append(cc)\n",
    "                        closeCountyList[cc].append(c)\n",
    "startTime = time.time()\n",
    "\n",
    "for i,t in enumerate(populatedTractList):\n",
    "    if i %400 == 0:\n",
    "        print(\"working on tract-tract distances for unit\",t,\"out of\",nHDs,\". Time =\",int(time.time() - startTime))\n",
    "    uuDist[t][t] == 0.\n",
    "    for tt in populatedTractList:\n",
    "        if tt > t and (HDcountyNo[tt] in closeCountyList[HDcountyNo[t]] or HDcountyNo[t] == HDcountyNo[tt]):  #time-saver; do the triangle matrix\n",
    "                dist = getLongDist(hdCP[t], hdCP[tt],xScale)\n",
    "                uuDist[t][tt], uuDist[tt][t] = dist, dist\n",
    "print(\"All done; total elapsed \",int(time.time()-startTime),\"seconds for\",STATE,\"with\",nDistricts,\"districts to map\" )\n",
    "plt.hist(uuDist)\n",
    "plt.show()\n",
    "print(\"our maxD was\",maxD)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "2f392acb-ba52-4343-80ae-a58ba0b57366",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "similar to above, but for angles\n",
      "working on unit-unit angles for unit 0 out of 6361 . Time = 0\n",
      "working on unit-unit angles for unit 200 out of 6361 . Time = 34\n",
      "working on unit-unit angles for unit 400 out of 6361 . Time = 69\n",
      "working on unit-unit angles for unit 600 out of 6361 . Time = 108\n",
      "working on unit-unit angles for unit 800 out of 6361 . Time = 149\n",
      "working on unit-unit angles for unit 1000 out of 6361 . Time = 184\n",
      "working on unit-unit angles for unit 1200 out of 6361 . Time = 218\n",
      "working on unit-unit angles for unit 1401 out of 6361 . Time = 250\n",
      "working on unit-unit angles for unit 1601 out of 6361 . Time = 281\n",
      "working on unit-unit angles for unit 1801 out of 6361 . Time = 308\n",
      "working on unit-unit angles for unit 2002 out of 6361 . Time = 333\n",
      "working on unit-unit angles for unit 2203 out of 6361 . Time = 360\n",
      "working on unit-unit angles for unit 2403 out of 6361 . Time = 386\n",
      "working on unit-unit angles for unit 2603 out of 6361 . Time = 409\n",
      "working on unit-unit angles for unit 2803 out of 6361 . Time = 433\n",
      "working on unit-unit angles for unit 3003 out of 6361 . Time = 461\n",
      "working on unit-unit angles for unit 3203 out of 6361 . Time = 482\n",
      "working on unit-unit angles for unit 3403 out of 6361 . Time = 502\n",
      "working on unit-unit angles for unit 3603 out of 6361 . Time = 522\n",
      "working on unit-unit angles for unit 3803 out of 6361 . Time = 542\n",
      "working on unit-unit angles for unit 4003 out of 6361 . Time = 557\n",
      "working on unit-unit angles for unit 4203 out of 6361 . Time = 575\n",
      "working on unit-unit angles for unit 4403 out of 6361 . Time = 589\n",
      "working on unit-unit angles for unit 4603 out of 6361 . Time = 602\n",
      "working on unit-unit angles for unit 4803 out of 6361 . Time = 614\n",
      "working on unit-unit angles for unit 5003 out of 6361 . Time = 622\n",
      "working on unit-unit angles for unit 5203 out of 6361 . Time = 629\n",
      "working on unit-unit angles for unit 5404 out of 6361 . Time = 635\n",
      "working on unit-unit angles for unit 5604 out of 6361 . Time = 639\n",
      "working on unit-unit angles for unit 5804 out of 6361 . Time = 643\n",
      "working on unit-unit angles for unit 6004 out of 6361 . Time = 645\n",
      "working on unit-unit angles for unit 6204 out of 6361 . Time = 647\n",
      "All done with angles; total elapsed seconds = 647\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#continuing option 2 \n",
    "print(\"similar to above, but for angles\")  #convention is angle[a][b] is from a to b\n",
    "uuAngle = [[0. for t in range(nHDs)] for t in range(nHDs)]\n",
    "\n",
    "pi = 3.141592653\n",
    "twoPi = pi*2.\n",
    "startTime = time.time()\n",
    "for i, t in enumerate(populatedTractList):\n",
    "    if i %200 == 0:\n",
    "        print(\"working on unit-unit angles for unit\",t,\"out of\",nHDs,\". Time =\",int(time.time() - startTime)  )\n",
    "    for tt in populatedTractList:\n",
    "        if tt > t and (HDcountyNo[tt] in closeCountyList[HDcountyNo[t]] or HDcountyNo[t] == HDcountyNo[tt]):  #time-saver; do the triangle matrix\n",
    "            angLE = math.atan2(hdCP[tt].y - hdCP[t].y, xScale * (hdCP[tt].x - hdCP[t].x) )\n",
    "            uuAngle[t][tt], uuAngle[tt][t] = angLE % twoPi, (angLE + pi) % twoPi\n",
    "print(\"All done with angles; total elapsed seconds =\",int(time.time()-startTime) )\n",
    "plt.hist(uuAngle)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "4cc54eba-ca37-4680-9699-37332133afb8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "774082.833 12 9288994.0 12.0 9288994.0\n",
      "9288994.0 9288994 0.9999999999999999\n"
     ]
    }
   ],
   "source": [
    "print(r3(aDP), nDistricts, statePop, statePop/aDP, trueStatePop)\n",
    "HDweight = [0 for t in range(nHDs)]\n",
    "for t in populatedTractList:\n",
    "    HDweight[t] = tractPop[t] / trueStatePop #skipping the cutList tracts\n",
    "print(statePop,np.sum([tractPop[t] for t in populatedTractList]), np.sum(HDweight)) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "dac2348a-060a-40a9-beeb-02ff70ec1aa1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RUN FOR ALL STATES.for extended peninsulas, need to broaden the 'neighborCountyList' to include all co-squished counties' neighbors\n"
     ]
    }
   ],
   "source": [
    "print(\"RUN FOR ALL STATES.for extended peninsulas, need to broaden the 'neighborCountyList' to include all co-squished counties' neighbors\")\n",
    "opt2nbrCtyList = [neighborCountyList[c].copy() for c in range(nCounties)]\n",
    "for i in range(nClips):\n",
    "    cList = toSquishCountiesList[i]\n",
    "    for c in cList:\n",
    "        for cc in cList:\n",
    "            for ccc in neighborCountyList[cc]:\n",
    "                if ccc not in opt2nbrCtyList[c] and ccc != c:\n",
    "                    opt2nbrCtyList[c].append(ccc)\n",
    "#for c in range(nCounties):\n",
    "#    for cc in opt2nbrCtyList[c]:\n",
    "#        plotPoly(countyGeom[cc])\n",
    "#    plotCenter(c,countyGeom[c])\n",
    "#    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "3873aaa2-0c39-4ac0-99c3-92dd7c18c555",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here is the main code to draw 4-wedge Home Districts for each populated HD centerpoint\n",
      "For each Home District, we will consider a wedge as one-from-full when it is within 1169.162 of targetWedgePop\n",
      "I am working on HD number 0 of 6361 HDs.  Elapsed sec = 0\n",
      "I am working on HD number 400 of 6361 HDs.  Elapsed sec = 58\n",
      "I am working on HD number 800 of 6361 HDs.  Elapsed sec = 116\n",
      "I am working on HD number 1200 of 6361 HDs.  Elapsed sec = 193\n",
      "I am working on HD number 1601 of 6361 HDs.  Elapsed sec = 267\n",
      "I am working on HD number 2002 of 6361 HDs.  Elapsed sec = 325\n",
      "I am working on HD number 2403 of 6361 HDs.  Elapsed sec = 412\n",
      "I am working on HD number 2803 of 6361 HDs.  Elapsed sec = 466\n",
      "I am working on HD number 3203 of 6361 HDs.  Elapsed sec = 539\n",
      "I am working on HD number 3603 of 6361 HDs.  Elapsed sec = 586\n",
      "I am working on HD number 4003 of 6361 HDs.  Elapsed sec = 640\n",
      "I am working on HD number 4403 of 6361 HDs.  Elapsed sec = 697\n",
      "I am working on HD number 4803 of 6361 HDs.  Elapsed sec = 760\n",
      "I am working on HD number 5203 of 6361 HDs.  Elapsed sec = 838\n",
      "I am working on HD number 5604 of 6361 HDs.  Elapsed sec = 930\n",
      "I am working on HD number 6004 of 6361 HDs.  Elapsed sec = 991\n",
      "1052.425 seconds elapsed. All done computing HD shapes and tractlists.  Here is a histogram of vtd usage.\n",
      "vtd avg and sd usage are 0.99967 0.11316\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAnYAAAHWCAYAAAD6oMSKAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/H5lhTAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAmJ0lEQVR4nO3df3TV9X348RcJJVGPSStoAjQu/kBRYaSCxNCeUWvasFJb2rMacRXGtDt21eLSaYEhYN0W3YrFCh1jh1Z3zhDKmeX0AIeWpvWoI8r4dVpOxaOrCEMTQGuicQZN7vcPv8amBMxF8oN3Ho9z7qn55P25eX/e5ceTz+fezx2UyWQyAQDAKS+nrycAAMDJIewAABIh7AAAEiHsAAASIewAABIh7AAAEiHsAAASIewAABIxuK8ncDK0t7fHiy++GGeeeWYMGjSor6cDAHDSZDKZeO2112LEiBGRk3P8c3JJhN2LL74YJSUlfT0NAIAes3///vjoRz963DFJhN2ZZ54ZEe8ccEFBQR/PBgDg5Glubo6SkpKO3jmeJMLu3cuvBQUFwg4ASFJ3Xm7mzRMAAIkQdgAAiRB2AACJEHYAAIkQdgAAiRB2AACJEHYAAIkQdgAAiRB2AACJEHYAAIkQdgAAiRB2AACJEHYAAIkQdgAAiRB2AACJEHYAAIkQdgAAiRjc1xMAek/pnA3dHrv3nqk9OBMAeoIzdgAAiRB2AACJEHYAAIkQdgAAiRB2AACJEHYAAIkQdgAAiRB2AACJcINioFe4OTJAz3PGDgAgEcIOACARwg4AIBHCDgAgEcIOACARwg4AIBHCDgAgEcIOACARblAMCcjm5r8p/WwAOhN2QJcEG8Cpx6VYAIBECDsAgEQIOwCARAg7AIBECDsAgEQIOwCARAg7AIBECDsAgEQIOwCARAg7AIBECDsAgEQIOwCARAg7AIBECDsAgEScUNgtW7YsSktLIz8/P8rLy2Pr1q3HHb927doYPXp05Ofnx9ixY2Pjxo2dvv8Xf/EXMWjQoE6PKVOmnMjUAAAGrKzDbs2aNVFTUxMLFy6MHTt2xLhx46KqqioOHjzY5fgtW7bE9OnT48Ybb4ydO3fGtGnTYtq0abF79+5O46ZMmRIvvfRSx+Phhx8+sSMCABigsg67++67L7761a/GrFmz4tJLL43ly5fH6aefHj/4wQ+6HH///ffHlClT4vbbb49LLrkk7r777rj88stj6dKlncbl5eVFcXFxx+MjH/nIiR0RAMAAlVXYHTlyJLZv3x6VlZXvPUFOTlRWVkZ9fX2X+9TX13caHxFRVVV11PhHH300zjnnnLj44ovja1/7Wrz88svZTA0AYMAbnM3gw4cPR1tbWxQVFXXaXlRUFHv27Olyn4aGhi7HNzQ0dHw9ZcqU+NKXvhTnnXde/M///E/Mmzcv/vRP/zTq6+sjNzf3qOdsbW2N1tbWjq+bm5uzOQwAgCRlFXY95brrruv477Fjx8Yf//EfxwUXXBCPPvpoXH311UeNr62tjbvuuqs3pwgA0O9ldSl22LBhkZubG42NjZ22NzY2RnFxcZf7FBcXZzU+IuL888+PYcOGxXPPPdfl9+fOnRtNTU0dj/3792dzGAAAScoq7IYMGRLjx4+Purq6jm3t7e1RV1cXFRUVXe5TUVHRaXxExObNm485PiLif//3f+Pll1+O4cOHd/n9vLy8KCgo6PQAABjosn5XbE1NTfzbv/1bPPTQQ/H000/H1772tWhpaYlZs2ZFRMSMGTNi7ty5HeNnz54dmzZtisWLF8eePXti0aJFsW3btrjlllsiIuL111+P22+/PZ588snYu3dv1NXVxRe+8IW48MILo6qq6iQdJgBA+rJ+jV11dXUcOnQoFixYEA0NDVFWVhabNm3qeIPEvn37IifnvV6cNGlSrFq1KubPnx/z5s2LUaNGxbp162LMmDEREZGbmxu/+tWv4qGHHopXX301RowYEZ/5zGfi7rvvjry8vJN0mAAA6RuUyWQyfT2JD6q5uTkKCwujqanJZVkGpNI5G/p6CifV3num9vUUAPqNbDrHZ8UCACRC2AEAJELYAQAkQtgBACRC2AEAJELYAQAkQtgBACRC2AEAJELYAQAkQtgBACRC2AEAJELYAQAkQtgBACRC2AEAJELYAQAkQtgBACRC2AEAJELYAQAkQtgBACRicF9PAOAPlc7Z0K1xe++Z2sMzATi1OGMHAJAIYQcAkAhhBwCQCGEHAJAIYQcAkAhhBwCQCGEHAJAIYQcAkAhhBwCQCGEHAJAIYQcAkAhhBwCQCGEHAJCIwX09AeDYSuds6OspAHAKccYOACARwg4AIBHCDgAgEcIOACARwg4AIBHCDgAgEcIOACARwg4AIBHCDgAgEcIOACARwg4AIBHCDgAgEcIOACARwg4AIBHCDgAgEcIOACARwg4AIBHCDgAgEcIOACARwg4AIBHCDgAgEcIOACARwg4AIBHCDgAgEcIOACARwg4AIBHCDgAgEcIOACARwg4AIBEnFHbLli2L0tLSyM/Pj/Ly8ti6detxx69duzZGjx4d+fn5MXbs2Ni4ceMxx958880xaNCgWLJkyYlMDQBgwMo67NasWRM1NTWxcOHC2LFjR4wbNy6qqqri4MGDXY7fsmVLTJ8+PW688cbYuXNnTJs2LaZNmxa7d+8+auyPf/zjePLJJ2PEiBHZHwkAwACXddjdd9998dWvfjVmzZoVl156aSxfvjxOP/30+MEPftDl+Pvvvz+mTJkSt99+e1xyySVx9913x+WXXx5Lly7tNO7AgQNx6623xn/8x3/Ehz70oRM7GgCAASyrsDty5Ehs3749Kisr33uCnJyorKyM+vr6Lvepr6/vND4ioqqqqtP49vb2uOGGG+L222+Pyy677H3n0draGs3NzZ0eAAAD3eBsBh8+fDja2tqiqKio0/aioqLYs2dPl/s0NDR0Ob6hoaHj63vvvTcGDx4c3/jGN7o1j9ra2rjrrruymTr0G6VzNvT1FABIVJ+/K3b79u1x//33x4MPPhiDBg3q1j5z586Npqamjsf+/ft7eJYAAP1fVmE3bNiwyM3NjcbGxk7bGxsbo7i4uMt9iouLjzv+8ccfj4MHD8a5554bgwcPjsGDB8cLL7wQ3/zmN6O0tLTL58zLy4uCgoJODwCAgS6rsBsyZEiMHz8+6urqOra1t7dHXV1dVFRUdLlPRUVFp/EREZs3b+4Yf8MNN8SvfvWr2LVrV8djxIgRcfvtt8dPf/rTbI8HAGDAyuo1dhERNTU1MXPmzJgwYUJMnDgxlixZEi0tLTFr1qyIiJgxY0aMHDkyamtrIyJi9uzZMXny5Fi8eHFMnTo1Vq9eHdu2bYsVK1ZERMTQoUNj6NChnX7Ghz70oSguLo6LL774gx4fAMCAkXXYVVdXx6FDh2LBggXR0NAQZWVlsWnTpo43SOzbty9yct47EThp0qRYtWpVzJ8/P+bNmxejRo2KdevWxZgxY07eUQAAEIMymUymryfxQTU3N0dhYWE0NTV5vR39nnfFnjx775na11M4qbr7ayO14waOL5vO6fN3xQIAcHIIOwCARAg7AIBECDsAgEQIOwCARAg7AIBECDsAgEQIOwCARAg7AIBECDsAgEQIOwCARAg7AIBEDO7rCQDQc0rnbOjWuL33TO3hmQC9wRk7AIBECDsAgEQIOwCARAg7AIBECDsAgEQIOwCARLjdCTAguO0HMBA4YwcAkAhhBwCQCGEHAJAIr7EDOAHdfc1ehNftAb3HGTsAgEQIOwCARAg7AIBEeI0dQA/L5vV4AB+EsANOWYIJoDOXYgEAEiHsAAASIewAABIh7AAAEiHsAAASIewAABIh7AAAEiHsAAAS4QbFAKcYN2YGjsUZOwCARAg7AIBECDsAgEQIOwCARAg7AIBECDsAgEQIOwCARAg7AIBECDsAgEQIOwCARAg7AIBE+KxYOEl8ficAfc0ZOwCARAg7AIBECDsAgEQIOwCARAg7AIBECDsAgEQIOwCARAg7AIBECDsAgEQIOwCARAg7AIBECDsAgEScUNgtW7YsSktLIz8/P8rLy2Pr1q3HHb927doYPXp05Ofnx9ixY2Pjxo2dvr9o0aIYPXp0nHHGGfGRj3wkKisr46mnnjqRqQEADFhZh92aNWuipqYmFi5cGDt27Ihx48ZFVVVVHDx4sMvxW7ZsienTp8eNN94YO3fujGnTpsW0adNi9+7dHWMuuuiiWLp0afz617+OJ554IkpLS+Mzn/lMHDp06MSPDABggBmUyWQy2exQXl4eV1xxRSxdujQiItrb26OkpCRuvfXWmDNnzlHjq6uro6WlJdavX9+x7corr4yysrJYvnx5lz+jubk5CgsL4+c//3lcffXV7zund8c3NTVFQUFBNocDJ03pnA19PQVOgr33TO3WuNT+/+7ucQO9L5vOyeqM3ZEjR2L79u1RWVn53hPk5ERlZWXU19d3uU99fX2n8RERVVVVxxx/5MiRWLFiRRQWFsa4ceOymR4AwIA2OJvBhw8fjra2tigqKuq0vaioKPbs2dPlPg0NDV2Ob2ho6LRt/fr1cd1118Ubb7wRw4cPj82bN8ewYcO6fM7W1tZobW3t+Lq5uTmbwwAASFK/eVfsVVddFbt27YotW7bElClT4tprrz3m6/Zqa2ujsLCw41FSUtLLswUA6H+yCrthw4ZFbm5uNDY2dtre2NgYxcXFXe5TXFzcrfFnnHFGXHjhhXHllVfGypUrY/DgwbFy5coun3Pu3LnR1NTU8di/f382hwEAkKSswm7IkCExfvz4qKur69jW3t4edXV1UVFR0eU+FRUVncZHRGzevPmY43//eX//cuvvy8vLi4KCgk4PAICBLqvX2EVE1NTUxMyZM2PChAkxceLEWLJkSbS0tMSsWbMiImLGjBkxcuTIqK2tjYiI2bNnx+TJk2Px4sUxderUWL16dWzbti1WrFgREREtLS3xD//wD/H5z38+hg8fHocPH45ly5bFgQMH4stf/vJJPFQAgLRlHXbV1dVx6NChWLBgQTQ0NERZWVls2rSp4w0S+/bti5yc904ETpo0KVatWhXz58+PefPmxahRo2LdunUxZsyYiIjIzc2NPXv2xEMPPRSHDx+OoUOHxhVXXBGPP/54XHbZZSfpMAEA0pf1fez6I/exoz9I7b5mA5X72AH9TY/dxw4AgP4r60uxAClL7UwcMLA4YwcAkAhhBwCQCGEHAJAIYQcAkAhhBwCQCGEHAJAItzsBoNu3eXEjY+jfhB28D/c1A+BU4VIsAEAihB0AQCKEHQBAIoQdAEAihB0AQCKEHQBAIoQdAEAihB0AQCKEHQBAIoQdAEAihB0AQCKEHQBAIoQdAEAihB0AQCKEHQBAIoQdAEAihB0AQCKEHQBAIoQdAEAihB0AQCKEHQBAIoQdAEAihB0AQCKEHQBAIoQdAEAihB0AQCKEHQBAIoQdAEAihB0AQCKEHQBAIoQdAEAihB0AQCKEHQBAIoQdAEAihB0AQCKEHQBAIgb39QQAOHWUztnQ7bF775nagzMBuuKMHQBAIoQdAEAihB0AQCKEHQBAIoQdAEAihB0AQCKEHQBAIoQdAEAihB0AQCKEHQBAIoQdAEAihB0AQCKEHQBAIoQdAEAiBvf1BKAvlM7Z0NdTAICTzhk7AIBEnFDYLVu2LEpLSyM/Pz/Ky8tj69atxx2/du3aGD16dOTn58fYsWNj48aNHd9766234lvf+laMHTs2zjjjjBgxYkTMmDEjXnzxxROZGgDAgJX1pdg1a9ZETU1NLF++PMrLy2PJkiVRVVUVzzzzTJxzzjlHjd+yZUtMnz49amtr43Of+1ysWrUqpk2bFjt27IgxY8bEG2+8ETt27Ig777wzxo0bF7/73e9i9uzZ8fnPfz62bdt2Ug6SgcMlVgAGskGZTCaTzQ7l5eVxxRVXxNKlSyMior29PUpKSuLWW2+NOXPmHDW+uro6WlpaYv369R3brrzyyigrK4vly5d3+TP++7//OyZOnBgvvPBCnHvuue87p+bm5igsLIympqYoKCjI5nBIjLCD/mPvPVP7egqQhGw6J6tLsUeOHInt27dHZWXle0+QkxOVlZVRX1/f5T719fWdxkdEVFVVHXN8RERTU1MMGjQoPvzhD3f5/dbW1mhubu70AAAY6LIKu8OHD0dbW1sUFRV12l5UVBQNDQ1d7tPQ0JDV+DfffDO+9a1vxfTp049ZpbW1tVFYWNjxKCkpyeYwAACS1K/eFfvWW2/FtddeG5lMJv7lX/7lmOPmzp0bTU1NHY/9+/f34iwBAPqnrN48MWzYsMjNzY3GxsZO2xsbG6O4uLjLfYqLi7s1/t2oe+GFF+IXv/jFca8h5+XlRV5eXjZTBwBIXlZn7IYMGRLjx4+Purq6jm3t7e1RV1cXFRUVXe5TUVHRaXxExObNmzuNfzfqnn322fj5z38eQ4cOzWZaAADECdzupKamJmbOnBkTJkyIiRMnxpIlS6KlpSVmzZoVEREzZsyIkSNHRm1tbUREzJ49OyZPnhyLFy+OqVOnxurVq2Pbtm2xYsWKiHgn6v7sz/4sduzYEevXr4+2traO19+dddZZMWTIkJN1rAAAScs67Kqrq+PQoUOxYMGCaGhoiLKysti0aVPHGyT27dsXOTnvnQicNGlSrFq1KubPnx/z5s2LUaNGxbp162LMmDEREXHgwIH4yU9+EhERZWVlnX7WL3/5y/jkJz95gocGADCwZH0fu/7Ifex4l/vYQf/hPnZwcvTYfewAAOi/hB0AQCKEHQBAIoQdAEAihB0AQCKEHQBAIoQdAEAihB0AQCKEHQBAIoQdAEAihB0AQCKEHQBAIoQdAEAihB0AQCKEHQBAIoQdAEAihB0AQCKEHQBAIoQdAEAihB0AQCIG9/UEABjYSuds6Na4vfdM7eGZwKnPGTsAgEQIOwCARAg7AIBECDsAgEQIOwCARAg7AIBEuN0Jp4Tu3g4BAAYyYQdAj/APMuh9LsUCACRC2AEAJELYAQAkQtgBACRC2AEAJELYAQAkQtgBACRC2AEAJELYAQAkQtgBACRC2AEAJMJnxdJnfI4kAJxcwg6AU0I2/xjce8/UHpwJ9F8uxQIAJELYAQAkQtgBACRC2AEAJELYAQAkQtgBACRC2AEAJELYAQAkQtgBACRC2AEAJELYAQAkQtgBACRC2AEAJELYAQAkQtgBACRC2AEAJELYAQAkQtgBACRC2AEAJELYAQAkYvCJ7LRs2bL453/+52hoaIhx48bFAw88EBMnTjzm+LVr18add94Ze/fujVGjRsW9994bn/3sZzu+/8gjj8Ty5ctj+/bt8corr8TOnTujrKzsRKYGAN1WOmdDt8btvWdqD88ETo6sz9itWbMmampqYuHChbFjx44YN25cVFVVxcGDB7scv2XLlpg+fXrceOONsXPnzpg2bVpMmzYtdu/e3TGmpaUlPvGJT8S999574kcCADDADcpkMplsdigvL48rrrgili5dGhER7e3tUVJSErfeemvMmTPnqPHV1dXR0tIS69ev79h25ZVXRllZWSxfvrzT2L1798Z5552X9Rm75ubmKCwsjKampigoKMjmcOhD3f2XMkC2unuGzRk7TgXZdE5WZ+yOHDkS27dvj8rKyveeICcnKisro76+vst96uvrO42PiKiqqjrmeAAATkxWr7E7fPhwtLW1RVFRUaftRUVFsWfPni73aWho6HJ8Q0NDllN9T2tra7S2tnZ83dzcfMLPBQCQilPyXbG1tbVRWFjY8SgpKenrKQEA9Lmswm7YsGGRm5sbjY2NnbY3NjZGcXFxl/sUFxdnNb475s6dG01NTR2P/fv3n/BzAQCkIquwGzJkSIwfPz7q6uo6trW3t0ddXV1UVFR0uU9FRUWn8RERmzdvPub47sjLy4uCgoJODwCAgS7r+9jV1NTEzJkzY8KECTFx4sRYsmRJtLS0xKxZsyIiYsaMGTFy5Miora2NiIjZs2fH5MmTY/HixTF16tRYvXp1bNu2LVasWNHxnK+88krs27cvXnzxxYiIeOaZZyLinbN9H+TMHgDAQJJ12FVXV8ehQ4diwYIF0dDQEGVlZbFp06aON0js27cvcnLeOxE4adKkWLVqVcyfPz/mzZsXo0aNinXr1sWYMWM6xvzkJz/pCMOIiOuuuy4iIhYuXBiLFi060WMDABhQsr6PXX/kPnanJvexA3qK+9iRkh67jx0AAP2XsAMASISwAwBIhLADAEhE1u+KhffjTREA0DecsQMASIQzdgAkx5UDBipn7AAAEiHsAAASIewAABIh7AAAEuHNE4k62Z9/6IXIAND/OWMHAJAIYQcAkAhhBwCQCK+xG+C8dg7g/WXzZ2V3X7sMPcEZOwCARAg7AIBECDsAgEQIOwCARAg7AIBECDsAgEQIOwCARAg7AIBECDsAgEQIOwCARAg7AIBECDsAgEQIOwCARAg7AIBECDsAgEQIOwCARAg7AIBEDO7rCQBASkrnbOjWuL33TO3hmTAQCTsAGGC6G58RAvRU41IsAEAihB0AQCKEHQBAIoQdAEAihB0AQCKEHQBAItzu5BSSzdvTAejf/JlOT3DGDgAgEcIOACARwg4AIBHCDgAgEcIOACARwg4AIBHCDgAgEcIOACARwg4AIBE+eQIAOKbufkLG3num9vBM6A5n7AAAEuGMHQDQa7L5jFxnAbPnjB0AQCKEHQBAIlyKBQBOad7g8R5hBwD0S9m8Ho93CLt+wC9cAOBkEHYAwAfmJEX/4M0TAACJEHYAAIkQdgAAiTihsFu2bFmUlpZGfn5+lJeXx9atW487fu3atTF69OjIz8+PsWPHxsaNGzt9P5PJxIIFC2L48OFx2mmnRWVlZTz77LMnMjUAgAEr6zdPrFmzJmpqamL58uVRXl4eS5YsiaqqqnjmmWfinHPOOWr8li1bYvr06VFbWxuf+9znYtWqVTFt2rTYsWNHjBkzJiIi/umf/im+973vxUMPPRTnnXde3HnnnVFVVRW/+c1vIj8//4Mf5UnkxaEAcGrqib/D+9u98QZlMplMNjuUl5fHFVdcEUuXLo2IiPb29igpKYlbb7015syZc9T46urqaGlpifXr13dsu/LKK6OsrCyWL18emUwmRowYEd/85jfjb//2byMioqmpKYqKiuLBBx+M66677n3n1NzcHIWFhdHU1BQFBQXZHE7WhB0A8K7eCLtsOierM3ZHjhyJ7du3x9y5czu25eTkRGVlZdTX13e5T319fdTU1HTaVlVVFevWrYuIiOeffz4aGhqisrKy4/uFhYVRXl4e9fX1XYZda2trtLa2dnzd1NQUEe8ceE9rb32jx38GAHBq6I32ePdndOdcXFZhd/jw4Whra4uioqJO24uKimLPnj1d7tPQ0NDl+IaGho7vv7vtWGP+UG1tbdx1111HbS8pKenegQAAnASFS3rvZ7322mtRWFh43DGn5A2K586d2+ksYHt7e7zyyisxdOjQGDRoUI/93Obm5igpKYn9+/f3+CXfU5216h7r1H3WqnusU/dZq+6xTt3XU2uVyWTitddeixEjRrzv2KzCbtiwYZGbmxuNjY2dtjc2NkZxcXGX+xQXFx93/Lv/29jYGMOHD+80pqysrMvnzMvLi7y8vE7bPvzhD2dzKB9IQUGBX9zdZK26xzp1n7XqHuvUfdaqe6xT9/XEWr3fmbp3ZXW7kyFDhsT48eOjrq6uY1t7e3vU1dVFRUVFl/tUVFR0Gh8RsXnz5o7x5513XhQXF3ca09zcHE899dQxnxMAgKNlfSm2pqYmZs6cGRMmTIiJEyfGkiVLoqWlJWbNmhURETNmzIiRI0dGbW1tRETMnj07Jk+eHIsXL46pU6fG6tWrY9u2bbFixYqIiBg0aFDcdttt8fd///cxatSojtudjBgxIqZNm3byjhQAIHFZh111dXUcOnQoFixYEA0NDVFWVhabNm3qePPDvn37IifnvROBkyZNilWrVsX8+fNj3rx5MWrUqFi3bl3HPewiIu64445oaWmJv/qrv4pXX301PvGJT8SmTZv63T3s8vLyYuHChUddBuZo1qp7rFP3WavusU7dZ626xzp1X39Yq6zvYwcAQP/ks2IBABIh7AAAEiHsAAASIewAABIh7P7AsmXLorS0NPLz86O8vDy2bt16zLGf/OQnY9CgQUc9pk7t+Q8E7g+yWauIiCVLlsTFF18cp512WpSUlMTf/M3fxJtvvtlLs+072azTW2+9Fd/+9rfjggsuiPz8/Bg3blxs2rSpF2fbNx577LG45pprYsSIETFo0KCOz5I+nkcffTQuv/zyyMvLiwsvvDAefPDBHp9nf5DtWr300ktx/fXXx0UXXRQ5OTlx22239co8+1q26/TII4/Epz/96Tj77LOjoKAgKioq4qc//WnvTLaPZbtWTzzxRHz84x+PoUOHxmmnnRajR4+O7373u70z2T50In9Oveu//uu/YvDgwcf84IWTSdj9njVr1kRNTU0sXLgwduzYEePGjYuqqqo4ePBgl+MfeeSReOmllzoeu3fvjtzc3Pjyl7/cyzPvfdmu1apVq2LOnDmxcOHCePrpp2PlypWxZs2amDdvXi/PvHdlu07z58+Pf/3Xf40HHnggfvOb38TNN98cX/ziF2Pnzp29PPPe1dLSEuPGjYtly5Z1a/zzzz8fU6dOjauuuip27doVt912W9x0000D4i/ibNeqtbU1zj777Jg/f36MGzeuh2fXf2S7To899lh8+tOfjo0bN8b27dvjqquuimuuuSb533sR2a/VGWecEbfccks89thj8fTTT8f8+fNj/vz5HfenTVW26/SuV199NWbMmBFXX311D83sD2ToMHHixMzXv/71jq/b2toyI0aMyNTW1nZr/+9+97uZM888M/P666/31BT7jWzX6utf/3rmU5/6VKdtNTU1mY9//OM9Os++lu06DR8+PLN06dJO2770pS9l/vzP/7xH59mfRETmxz/+8XHH3HHHHZnLLrus07bq6upMVVVVD86s/+nOWv2+yZMnZ2bPnt1j8+mvsl2nd1166aWZu+666+RPqB870bX64he/mPnKV75y8ifUT2WzTtXV1Zn58+dnFi5cmBk3blyPziuTyWScsfv/jhw5Etu3b4/KysqObTk5OVFZWRn19fXdeo6VK1fGddddF2eccUZPTbNfOJG1mjRpUmzfvr3jMuRvf/vb2LhxY3z2s5/tlTn3hRNZp9bW1qNuzH3aaafFE0880aNzPdXU19d3WteIiKqqqm7/XoX3097eHq+99lqcddZZfT2Vfm/nzp2xZcuWmDx5cl9Ppd/54Q9/GL/97W9j4cKFvfYzs/7kiVQdPnw42traOj5B411FRUWxZ8+e991/69atsXv37li5cmVPTbHfOJG1uv766+Pw4cPxiU98IjKZTLz99ttx8803J30p9kTWqaqqKu677774kz/5k7jggguirq4uHnnkkWhra+uNKZ8yGhoaulzX5ubm+L//+7847bTT+mhmpOI73/lOvP7663Httdf29VT6rY9+9KNx6NChePvtt2PRokVx00039fWU+pVnn3025syZE48//ngMHtx7ueWM3UmycuXKGDt2bEycOLGvp9IvPfroo/GP//iP8f3vfz927NgRjzzySGzYsCHuvvvuvp5av3L//ffHqFGjYvTo0TFkyJC45ZZbYtasWZ0+pg/oWatWrYq77rorfvSjH8U555zT19Pptx5//PHYtm1bLF++PJYsWRIPP/xwX0+p32hra4vrr78+7rrrrrjooot69Wc7Y/f/DRs2LHJzc6OxsbHT9sbGxiguLj7uvi0tLbF69er49re/3ZNT7DdOZK3uvPPOuOGGGzr+RTd27NiOzwf+u7/7uyTD5UTW6eyzz45169bFm2++GS+//HKMGDEi5syZE+eff35vTPmUUVxc3OW6FhQUOFvHB7J69eq46aabYu3atUdd7qez8847LyLe+fO8sbExFi1aFNOnT+/jWfUPr732Wmzbti127twZt9xyS0S8c3k/k8nE4MGD42c/+1l86lOf6pGfnd7fpidoyJAhMX78+Kirq+vY1t7eHnV1dVFRUXHcfdeuXRutra3xla98paen2S+cyFq98cYbR8Vbbm5uRERkEv244g/yayo/Pz9GjhwZb7/9dvznf/5nfOELX+jp6Z5SKioqOq1rRMTmzZvfd13heB5++OGYNWtWPPzwwwPmtlUnS3t7e7S2tvb1NPqNgoKC+PWvfx27du3qeNx8881x8cUXx65du6K8vLzHfrYzdr+npqYmZs6cGRMmTIiJEyfGkiVLoqWlJWbNmhURETNmzIiRI0dGbW1tp/1WrlwZ06ZNi6FDh/bFtPtEtmt1zTXXxH333Rcf+9jHory8PJ577rm4884745prrukIvBRlu05PPfVUHDhwIMrKyuLAgQOxaNGiaG9vjzvuuKMvD6PHvf766/Hcc891fP3888/Hrl274qyzzopzzz035s6dGwcOHIh///d/j4iIm2++OZYuXRp33HFH/OVf/mX84he/iB/96EexYcOGvjqEXpPtWkVE7Nq1q2PfQ4cOxa5du2LIkCFx6aWX9vb0e02267Rq1aqYOXNm3H///VFeXh4NDQ0R8c6blwoLC/vkGHpLtmu1bNmyOPfcc2P06NER8c6tYr7zne/EN77xjT6Zf2/JZp1ycnJizJgxnfY/55xzIj8//6jtJ12Pv+/2FPPAAw9kzj333MyQIUMyEydOzDz55JMd35s8eXJm5syZncbv2bMnExGZn/3sZ708076XzVq99dZbmUWLFmUuuOCCTH5+fqakpCTz13/915nf/e53vT/xXpbNOj366KOZSy65JJOXl5cZOnRo5oYbbsgcOHCgD2bdu375y19mIuKox7trM3PmzMzkyZOP2qesrCwzZMiQzPnnn5/54Q9/2Ovz7gsnslZdjf+jP/qjXp97b8p2nSZPnnzc8SnLdq2+973vZS677LLM6aefnikoKMh87GMfy3z/+9/PtLW19c0B9JIT+b33+3rrdieDMplEr4MBAAwwXmMHAJAIYQcAkAhhBwCQCGEHAJAIYQcAkAhhBwCQCGEHAJAIYQcAkAhhBwCQCGEHAJAIYQcAkAhhBwCQiP8Ha1rIpPTpI3wAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here are your HD pops\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#continuing option 2 .......\n",
    "# BELOW modified Dec23 to use inter-unit distances and angles, (counties still wedgeIntersxn) otherwise similar to HD2\n",
    "# --THIS ESSENTIALLY TAKES THE ORIGINAL TRACT-BASED HD centerpoints, and redraws HD2 districts after convexifying corners and convex_hull\n",
    "print(\"Here is the main code to draw 4-wedge Home Districts for each populated HD centerpoint\") \n",
    "#this is a hybrid of HD2 and the organic code, in that all wedge tracts must be in a chain of neighboring counties\n",
    "#General sequence: draw 4 equi-angle wedges with random starting orientation.  If not all can fill a quarter aDP ...\n",
    "# ... find the closest map boundary point to the tract center point in the shortest wedge.  Orient the 0th wedge to face this point\n",
    "# ... determine the \"maxWedgePop\" for this short wedge and the other three wedges extended past the boundary\n",
    "# ...  if this results in only one short wedge, or opposing short wedges, adjust wedge angles\n",
    "# Regardless of whether we re-oriented or adjusted angles, compute each wedgePop for infinite radius\n",
    "#   ... then adjust other targetWedgePops if some found to be short.\n",
    "#   ... for non-shorted wedges, use bisection method to adjust radius to meet targetWedgePop\n",
    "#   ... once total HDpop within tolerance, add/subtract a tract fraction to fulfill HDpop\n",
    "#  create a list of fully used tracts per HD, save the tract# of the split tract and its fractional use\n",
    "#  Compute tractUse across all HDs at the end from the tractUsageLists.  Defer patching and partisan calcs to another code\n",
    "\n",
    "pi=3.1415926536\n",
    "#MAPhull = MAP.convex_hull #used for exitAngle calc.  Defined in an above block to allow user modification\n",
    "nWedges = 4  #number of wedges per home district polygon  \n",
    "avgWedgeAngle = 2.*pi / nWedges\n",
    "angle, angle2, wedgePoly = [0.]*nWedges, [0.]*nWedges, [dummyPoly]*nWedges  #start and stop angle of each wedge\n",
    "pt1, pt2, pt3 = [Point(0,0)]*nWedges, [Point(0,0)]*nWedges, [Point(0,0)]*nWedges #these four define the polygon wedge for a growing home district\n",
    "tractUse = [0.] * nHDs  #this will store how much we use this tract in ALL HD's vs. expectation\n",
    "HDtractList = [list()]*nHDs\n",
    "splitTractNo = [-999]*nHDs  #the tract that is only partially used to finish each HD\n",
    "splitTractUse = [0.]*nHDs  #and this is what fraction of the split tract is included\n",
    "HDvPop = [0.]*nHDs\n",
    "#HDweight = [tractPop[t] / (statePop - excludedPop) for t in range(nTracts)]  #relative weight of each drawn HD\n",
    "HDPoly1 = [dummyPoly]*nHDs  #final 4-wedge shape, unionized from blockgroups / tracts\n",
    "HDarea = [0.]*nHDs  #geographical area of each home district (after boundary trim)\n",
    "HDradius = [[0.]*nWedges for t in range(nHDs)] #final wedge length for each Home District wedge\n",
    "HDangle = [[0.]*nWedges for t in range(nHDs)] #final starting angle for each HD wedge\n",
    "angle0 = [-999.] * nHDs  #orientation of 0th wedge.  Random except re-oriented if we are near-boundary\n",
    "avgTractPop = statePop/len(populatedTractList)\n",
    "tolerPops = [0.8 * avgTractPop, 0.5 * np.max(tractPop)]  #threshold gap before adding one more unit to a wedge \n",
    "tolerPop = tolerPops[0]\n",
    "print(\"For each Home District, we will consider a wedge as one-from-full when it is within\",r3(tolerPops[0]),\"of targetWedgePop\")\n",
    "tractPrintInterval = 400  #for tracking progress\n",
    "levelL = 0.36 #sqrt(pop) for angle=std  These two control distortion in wedge angles relative to wedgePop shortness\n",
    "maxAngleRatio = 1.9  #for tightening tract weighting near boundaries  #HD2\n",
    "maxAngle = 1.8*pi/2. # limit to avoid wedges too close to half a pie\n",
    "minAdjRatio = 0.5  #min ratio of pop of adjacent wedge (to min wedge) to targetWedgePop to not consider this a corner HD\n",
    "maxUncap = 0.5 #the max ratio of uncaptured pop in a maxWedge vs. target wedge pop that we will not stretch to include (7/23)\n",
    "oppWt = 0.0    #the fraction of gap between normal targetWedgePop and the minWedgePop that we allow the opposite wedge to add to tgtPop = minWedgePop\n",
    "maxWedgePop = [0.] * nWedges  #wedge pop if we explode wedge to maximum radius\n",
    "printDebug = \"no\"\n",
    "codeStartTime = time.time()\n",
    "hdCPpop = [HDweight[t] * statePop for t in range(nHDs)]\n",
    "countyHDlist = [list() for c in range(nCounties)]\n",
    "for t in populatedTractList:\n",
    "    countyHDlist[HDcountyNo[t]].append(t)\n",
    "\n",
    "for kkkj, t in enumerate(populatedTractList):  #range(nTracts) : #loop on each tract. \n",
    "    hC = HDcountyNo[t]     #this tract's home county\n",
    "    HDtractList[t] = [t] #seed the list of tracts in this HD\n",
    "    wedgeList = [list() for w in range(nWedges)]   #list of each wedge's tracts, excluding home tract\n",
    "    barredList = list()  #list of wedge numbers for which we are barred from altering their targetWedgePops\n",
    "    if (kkkj % tractPrintInterval) == 0 : \n",
    "        print(\"I am working on HD number {0} of {1} HDs.  Elapsed sec = {2}\".format(t,nHDs,int(time.time()-codeStartTime) ) )  \n",
    "    nActiveWedges = nWedges #active wedges have not run over boundary\n",
    "    wedgePop = [0.]*nWedges\n",
    "    targetWedgePop = [aDP / nWedges]*nWedges  #at beginning, split districtPop equally among wedges\n",
    "    \n",
    "    angle0[t] = random.uniform(0,2.*pi)  #imparts random orientation to the midangle of our starting wedge\n",
    "    wedgeAngle = [avgWedgeAngle for w in range(nWedges) ] #reset to equi-angle when starting each tract\n",
    "    for nW in range(nWedges-1):\n",
    "        wedgeAngle[nW] += random.uniform(-0.0001,0.0001)  #this wiggle solves a later indexing ambiguity for corner tracts\n",
    "    wedgeAngle[nWedges-1] = 2.*pi - (np.sum(wedgeAngle) - wedgeAngle[nWedges-1] ) #squaring up to 2pi total\n",
    "    startAngle = [angle0[t] for nW in range(nWedges)]\n",
    "    for nW in range(1,nWedges):\n",
    "        startAngle[nW] = startAngle[nW-1] + wedgeAngle[nW-1]\n",
    "    endAngle = [startAngle[nW] + wedgeAngle[nW] for nW in range(nWedges)]\n",
    "    #  TRIAL LOOP TO SEE WHICH WEDGES CAN FILL TO TARGET POP w/equiangle wedges\n",
    "    maxWedgePoly = [ buildWedge(hdCP[t],startAngle[nW],endAngle[nW], maxD, xScale) for nW in range(nWedges) ]    \n",
    "    maxWedgePop =[ hdCPpop[t]*wedgeAngle[nW]/(2.*pi) for nW in range(nWedges) ]  #seed wedge with fraction of its home tract pop\n",
    "    willFill = [0] * nWedges #would this wedge meet its target with infinite radius?\n",
    "    for nW in range(nWedges):   #... then add in-county Pop and wedge Pop from contiguous chain of counties\n",
    "        iCP, Li   = getCountyWP(t,maxWedgePoly[nW], hdCP, hdCPpop, countyHDlist[hC])\n",
    "        #nonCP, Ln = getNonCWP(maxWedgePoly[nW], hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyList) \n",
    "        nonCP, Ln = getNonCWP_c(startAngle[nW],endAngle[nW], hC, hdCP, hdCPpop, countyGeom, countyPop, countyHDlist,\n",
    "                                opt2nbrCtyList, uuDist[t], uuAngle[t], maxWedgePoly[nW])\n",
    "        maxWedgePop[nW] += (iCP + nonCP)\n",
    "        wedgeList[nW] = Li + Ln\n",
    "        if maxWedgePop[nW] > targetWedgePop[nW]:\n",
    "            willFill[nW] = 1\n",
    "     \n",
    "    if np.sum(willFill) < nWedges:  #at least one wedge couldn't reach its wedgePop target (went over boundary) ...\n",
    "        minW = maxWedgePop.index(np.min(maxWedgePop)) #.. so we will orient the 0th wedge to face the shortest wedgePop's closest boundary\n",
    "        exitAngle = getExitAngle(hdCP[t],maxWedgePoly[minW], MAPhull, startAngle[minW], endAngle[minW])\n",
    "        angle0[t] = exitAngle - 0.5*(2.*pi / nWedges)  #Now reset all angles based on new starting orientation.  All wedge angles still equal\n",
    "        startAngle = [angle0[t] for nW in range(nWedges)]\n",
    "        for nW in range(1,nWedges):\n",
    "            startAngle[nW] = startAngle[nW-1] + wedgeAngle[nW-1]\n",
    "        endAngle = [startAngle[nW] + wedgeAngle[nW] for nW in range(nWedges)]\n",
    "        maxWedgePoly = [buildWedge(hdCP[t],startAngle[nW],endAngle[nW], maxD, xScale) for nW in range(nWedges) ]\n",
    "        \n",
    "        willFill = [0]*nWedges\n",
    "        #Now re-calc each maxWedgePop if we extend wedge's radius past map with new angle0 orientation (wedge angles still constant)\n",
    "        maxWedgePop =[ hdCPpop[t]*wedgeAngle[nW]/(2.*pi) for nW in range(nWedges) ]  #seed wedge with fraction of its home tract pop        \n",
    "        for nW in range(nWedges):   #... then add in-county and nonCounty wedge Pop from contiguous chain of counties\n",
    "            iCP, Li   = getCountyWP(t,maxWedgePoly[nW], hdCP, hdCPpop, countyHDlist[hC])\n",
    "            #nonCP, Ln = getNonCWP(maxWedgePoly[nW], hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyList)\n",
    "            nonCP, Ln = getNonCWP_c(startAngle[nW],endAngle[nW], hC, hdCP, hdCPpop, countyGeom, countyPop, countyHDlist,\n",
    "                                    opt2nbrCtyList, uuDist[t], uuAngle[t], maxWedgePoly[nW])\n",
    "            maxWedgePop[nW] += (iCP + nonCP)\n",
    "            wedgeList[nW] = Li + Ln\n",
    "            if maxWedgePop[nW] > targetWedgePop[nW]:\n",
    "                willFill[nW] = 1       \n",
    "    \n",
    "    if np.sum(willFill) < nWedges:  #check if we need to modify wedge angles after possible re-orientation.  \n",
    "        # If so, re-draw maxWedgePoly's, re-calc maxWedgePops\n",
    "        nUnfilledWedges = nWedges - np.sum(willFill)\n",
    "        isChange, newInclA = getNewAngles(maxWedgePop, targetWedgePop, aDP, levelL, minAdjRatio, maxAngle, maxAngleRatio, nUnfilledWedges )\n",
    "        if isChange: #no longer equi-angle\n",
    "            newStartAngle = [0.5*(startAngle[nW]+endAngle[nW]) - 0.5*newInclA[nW] for nW in range(nWedges) ]\n",
    "            newEndAngle =   [0.5*(startAngle[nW]+endAngle[nW]) + 0.5*newInclA[nW] for nW in range(nWedges) ]\n",
    "            startAngle, endAngle, wedgeAngle = newStartAngle.copy(), newEndAngle.copy(), newInclA.copy()\n",
    "            maxWedgePoly = [ buildWedge(hdCP[t],startAngle[nW],endAngle[nW], \n",
    "                                        maxD/math.cos(0.5*wedgeAngle[nW]), xScale ) for nW in range(nWedges) ]\n",
    "            willFill = [0]*nWedges\n",
    "            #Now re-calc each maxWedgePop if we extend wedge's radius past map with new angle0 orientation and new wedge angles\n",
    "            maxWedgePop =[ hdCPpop[t]*wedgeAngle[nW]/(2.*pi) for nW in range(nWedges) ]  #seed wedge with fraction of its home tract pop\n",
    "            for nW in range(nWedges):   #... then add in-county Pop and wedge Pop from contiguous chain of counties\n",
    "                iCP, Li   = getCountyWP(t,maxWedgePoly[nW], hdCP, hdCPpop, countyHDlist[hC])                \n",
    "                #nonCP, Ln = getNonCWP(maxWedgePoly[nW], hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyList)\n",
    "                nonCP, Ln = getNonCWP_c(startAngle[nW],endAngle[nW], hC, hdCP, hdCPpop, countyGeom, countyPop, countyHDlist,\n",
    "                                        opt2nbrCtyList, uuDist[t], uuAngle[t], maxWedgePoly[nW])\n",
    "                maxWedgePop[nW] += (iCP + nonCP)\n",
    "                wedgeList[nW] = Li + Ln\n",
    "            minW = wedgeAngle.index(np.max(wedgeAngle)) #should be 0th wedge, but playing it safe.  This is the 1st wide-angle wedge ..\n",
    "            oppW = int(int(minW+nWedges/2)%nWedges)   #and its opposite\n",
    "            if maxWedgePop[minW] > maxWedgePop[oppW] and maxWedgePop[oppW] < aDP / nWedges:  #minW and oppW are flipped after inclA adjmt\n",
    "                oppW = minW\n",
    "                minW = int(int(minW+nWedges/2)%nWedges)\n",
    "            if maxWedgePop[minW] < targetWedgePop[oppW]:  #we need to constrain oppW in this HD2 implementation; redistribute tgt to adjacents\n",
    "                maxNonOppW = np.sum(maxWedgePop) - maxWedgePop[oppW] #...but only if other wedges can pick up slack; need to check\n",
    "                minOppWedgePop = aDP - maxNonOppW  #cannot set oppW target below this or we won't reach aDP across all wedges\n",
    "                barredList = [oppW]\n",
    "                targetWedgePop[oppW] = max(minOppWedgePop, maxWedgePop[minW] + oppWt * (targetWedgePop[oppW] - maxWedgePop[minW]) )\n",
    "                tWPgap = aDP / float(nWedges) - targetWedgePop[oppW] \n",
    "                for nW in range(nWedges):\n",
    "                    if nW != minW and nW != oppW:\n",
    "                        targetWedgePop[nW] += tWPgap/float(nWedges - 2.)  #if oppW target is limited, allot to adjacent wedges\n",
    "            for nW in range(nWedges):\n",
    "                if maxWedgePop[nW] > targetWedgePop[nW]:\n",
    "                    willFill[nW] = 1  \n",
    "    \n",
    "    if abs(np.sum(targetWedgePop) / aDP - 1.) > 0.001:\n",
    "        raise Exception(\"FAIL! Our target wedgepops\",targetWedgePop, np.sum(targetWedgePop),\"no longer add up to\",aDP)\n",
    "    \n",
    "    if np.sum(willFill) == nWedges:  #all wedges will fill.  Will any leave a small near-boundary remnant?  If so, pick up smallest remnant\n",
    "        remnantWedgePopFrac = [ ( maxWedgePop[w] - targetWedgePop[w] )/targetWedgePop[w] for w in range(nWedges) ]\n",
    "        if np.min(remnantWedgePopFrac) < maxUncap :  #lessen tWP's of *adjacent* wedges, then increase this wedge's target --> max\n",
    "            minW = remnantWedgePopFrac.index(np.min(remnantWedgePopFrac))\n",
    "            oppW = int((minW+nWedges/2)%nWedges)\n",
    "            #print(\"filling to boundary for tract,wedge, tWP, mWP =\",t,minW, r3(targetWedgePop[minW]), maxWedgePop[minW])\n",
    "            for nW in range(nWedges):\n",
    "                if nW != minW and nW != oppW:\n",
    "                    targetWedgePop[nW] -= (remnantWedgePopFrac[minW] * targetWedgePop[minW] ) / (nWedges - 2.)\n",
    "            targetWedgePop[minW] = maxWedgePop[minW]\n",
    "            #       OK, READY TO SOLVE FOR NON-FILLED WEDGE SIZES once we adjust targets for unfilled wedges\n",
    "    #print(t,\" prior to rebalanceTWP call, mWPs, tWPs are\",maxWedgePop, targetWedgePop)\n",
    "    targetWedgePop, willFill = rebalanceTWPs(maxWedgePop, targetWedgePop, barredList)\n",
    "    #if np.max(targetWedgePop) - np.min(targetWedgePop) > 0.02 * aDP: #debug\n",
    "    #    print(\"for tract\",t,\",  After rebalancing but before tweaks for blocky pop adds: willFill, targetWedgePops and maxWedgePops are ...\")\n",
    "    #    for w in range(nWedges):\n",
    "    #        print(w, willFill[w],r3(targetWedgePop[w]),int(maxWedgePop[w]) )\n",
    "    for w in range(nWedges):  #WHEW!  WE CAN FINALLY ASSIGN ALL WEDGES' POPS AND TRACTLISTS\n",
    "        loop = 0\n",
    "        if willFill[w] == 0:  #wedge is maxed out\n",
    "            wedgePop[w] = maxWedgePop[w]\n",
    "            #wedgeList[w] = ...  #we already captured this list = maxWedge list\n",
    "            HDradius[t][w] = maxD/math.cos(0.5*wedgeAngle[w])\n",
    "        else:  #need to solve for wedge radius to meet targetPop.  Use bisection as scipy minimize no faster\n",
    "            HDcpWP = hdCPpop[t] * wedgeAngle[w]/(2.*pi)\n",
    "            nonHDcpTWP = targetWedgePop[w] - HDcpWP\n",
    "            #wedgePop[w], wedgeList[w], HDradius[t][w] = solveWedgeB(nontractTWP,t,hC,maxWedgePoly[w],tolerPop,tractCP, tractPop,\n",
    "            #                                                        countyNo,countyTractList,countyGeom, neighborCountyList,uuDist[t])\n",
    "            wedgePop[w], wedgeList[w], HDradius[t][w] = solveWedgeC(nonHDcpTWP,t,hC, maxWedgePoly[w],startAngle[w], endAngle[w], tolerPop,\n",
    "                                                                    hdCP, hdCPpop,HDcountyNo, countyHDlist,countyGeom,\n",
    "                                                                    opt2nbrCtyList,uuDist[t],uuAngle[t])\n",
    "            popGap = nonHDcpTWP - wedgePop[w]  #gap between target and solved wedge pop; can be negative\n",
    "            notYetAdjusted, nextW = True, w+1  #looking to adjust a later wedge's target pop to minimize drift in total HD pop\n",
    "            while notYetAdjusted and nextW < nWedges:\n",
    "                if willFill[nextW] == 1 and maxWedgePop[nextW] > targetWedgePop[nextW] + popGap :  #can accommodate\n",
    "                    targetWedgePop[nextW] += popGap\n",
    "                    notYetAdjusted = False\n",
    "                nextW +=1          \n",
    "\n",
    "        HDangle[t][w] = startAngle[w]\n",
    "    #print(t,\"tract. After TWP adjustment, targetWedgePops are\",targetWedgePop)\n",
    "    HDtractList[t] = [t]\n",
    "    totPop = hdCPpop[t]\n",
    "    for nW in range(nWedges):\n",
    "        for tt in wedgeList[nW]:\n",
    "            HDtractList[t].append(tt)  #building the list of tracts in the Home District  (we'll keep up with below changes)\n",
    "            totPop += hdCPpop[tt]\n",
    "    offsetPop = totPop - aDP  #we have solved for all wedge radii to get each within one tractPop of target ... \n",
    "    HDvPop[t] = totPop\n",
    "    #if offsetPop > 0:   #... now include a splitPoly to nail the avg District Pop\n",
    "    #    isOver = True  #we slightly overshot.  ID the farthest-away tract for split-jettison\n",
    "    #    splitTractNo[t], splitTractUse[t] = getPartialTract(t, HDtractList[t], offsetPop, uuDist[t], hdCPpop, neighborList)\n",
    "    #    HDvPop[t] = totPop - (1. - splitTractUse[t]) * tractPop[splitTractNo[t]]\n",
    "    #if offsetPop < 0:\n",
    "    #    isOver = False  #we have undershot.  Pick up the nearest contiguous tract that can be split to fill the gap\n",
    "    #    splitTractNo[t], splitTractUse[t] = getPartialTract(t, HDtractList[t], offsetPop, uuDist[t], tractPop, neighborList)\n",
    "    #    HDtractList[t].append(splitTractNo[t])\n",
    "    #    HDvPop[t] = totPop + splitTractUse[t]*tractPop[splitTractNo[t]]       \n",
    "    #if abs(1. - HDvPop[t]/aDP) > 0.005 :  #something went wrong with pop assignation for this HD\n",
    "    #    print(\"WARNING! Total Home District pop was\",HDvPop[t],\"vs target\",aDP,\"for tract\",t)   ##### hdCP topology not yet known; skip partial\n",
    "        \n",
    "    HDPoly1[t] = dummyPoly  #tractGeom[t] #skip constructing the HD poly shape.  Do compute area of the Home District, including final partial\n",
    "    HDarea[t] = 0.\n",
    "    for tt in HDtractList[t]:\n",
    "        if tt == splitTractNo[t]:\n",
    "            tractUse[tt] += nDistricts * HDweight[t] * splitTractUse[t] \n",
    "            #HDarea[t]   += tractArea[tt] * splitTractUse[t]  #these are original (nonsquished) areas\n",
    "            \n",
    "        else:\n",
    "            tractUse[tt] += nDistricts * HDweight[t]\n",
    "            #HDarea[t]    += tractArea[tt]\n",
    "            #HDPoly1[t] = HDPoly1[t].union(tractGeom[tt])\n",
    "    HDPoly1[t] = buildPoly(hdCP[t],HDradius[t], HDangle[t] )\n",
    "    #HDarea[t] = HDPoly1[t].area + splitTractUse[t] * tractArea[splitTractNo[t]]  \n",
    "    #if splitTractUse[t] > 0.5:\n",
    "    #    HDPoly1[t] = HDPoly1[t].union(tractGeom[splitTractNo[t]])\n",
    "                          \n",
    "    #ALL DONE ESTABLISHING THE FINAL HDTRACTLIST.  FINALIZE STATS\n",
    "totalTime = time.time() - codeStartTime\n",
    "print(r3(totalTime),\"seconds elapsed. All done computing HD shapes and tractlists.  Here is a histogram of vtd usage.\")\n",
    "n_bins=50\n",
    "popTractUse, plotWts = [tractUse[t] for t in populatedTractList], [HDweight[t] for t in populatedTractList]\n",
    "\n",
    "origHDuseAvg, origHDuseSD = getWeightedAvgAndSD(tractUse,HDweight)\n",
    "print(\"vtd avg and sd usage are\",r5(origHDuseAvg), r5(origHDuseSD) )\n",
    "\n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "ax.hist(popTractUse, bins=n_bins, weights=plotWts)\n",
    "plt.show()\n",
    "HDvPop = [np.sum([hdCPpop[tt] for tt in HDtractList[t]]) for t in range(nHDs)]\n",
    "plt.scatter([hdCPpop[t] for t in populatedTractList],[HDvPop[t] for t in populatedTractList] )\n",
    "print(\"here are your HD pops\")\n",
    "plt.show()\n",
    "origHDHDtractList = [HDtractList[t].copy() for t in range(nHDs)] #save for posterity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "37c238bb-b340-431b-ad11-95e4409d9699",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now we will write the polygon-based results to a file\n"
     ]
    }
   ],
   "source": [
    "#last block of option 2 (i.e. generating polygonal HDs from scratch)\n",
    "print(\"Now we will write the polygon-based results to a file\")\n",
    "tractNo = [t for t in range(nHDs) ]\n",
    "HDangle0 = [HDangle[t][0] for t in range(nHDs) ]\n",
    "HDangle1 = [HDangle[t][1] for t in range(nHDs) ]\n",
    "HDangle2 = [HDangle[t][2] for t in range(nHDs) ]\n",
    "HDangle3 = [HDangle[t][3] for t in range(nHDs) ]\n",
    "HDradius0 = [HDradius[t][0] for t in range(nHDs)]\n",
    "HDradius1 = [HDradius[t][1] for t in range(nHDs)]\n",
    "HDradius2 = [HDradius[t][2] for t in range(nHDs)]\n",
    "HDradius3 = [HDradius[t][3] for t in range(nHDs)]\n",
    "hdCPx, hdCPy =   [hdCP[t].x for t in range(nHDs)], [hdCP[t].y for t in range(nHDs)]\n",
    "\n",
    "paramList = [\"STATE\",\"statePop\",\"nDistricts\",\"nHDs\",\"nWedges\",\"popn-toler\",\"levelL\", \"maxAngleRatio\",\n",
    "             \"maxAngle\",\"minAdjRatio\",\"maxUncap\", \"oppWt\", \"calc sec\",\"xScale\",\"outputs...\"]\n",
    "paramValues = [STATE,statePop, nDistricts, nHDs, nWedges, tolerPop, levelL, maxAngleRatio, maxAngle, minAdjRatio, maxUncap,\n",
    "               oppWt, totalTime, xScale, -777]\n",
    "for i in range(nHDs-len(paramList)):\n",
    "    paramList.append(\".\")\n",
    "    paramValues.append(-99)  #so all columns have same number of entries, even the parameter list\n",
    "HDdf = pd.DataFrame( {\"paramList\": paramList,\"paramValues\":paramValues,\"countyNo\":HDcountyNo,\n",
    "                    \"tractNo\":tractNo,\"centroid x\":hdCPx,\"centroid y\":hdCPy,\"tractPop\":hdCPpop,\n",
    "                    \"HDweight\":HDweight,\"HD-pop\":HDvPop,\"HDarea\":HDarea, \"countyNo\":countyNo,\n",
    "                    \"startAngle\":angle0,\"HDangle0\":HDangle0,\"HDangle1\":HDangle1,\"HDangle2\":HDangle2,\"HDangle3\":HDangle3,\n",
    "                    \"HDradius0\":HDradius0,\"HDradius1\":HDradius1,\"HDradius2\":HDradius2, \"HDradius3\":HDradius3,\"tractUse\":tractUse,\n",
    "                    \"splitTractNo\":splitTractNo,\"splitTractUse\":splitTractUse,\"HDtractList\":HDtractList} ) \n",
    "\n",
    "#outname = STATE+str(int(nTracts))+\"HD2Bnopatch\"+str(int(nDistricts))+\"nW4.csv\"  #solveWedgeB\n",
    "outname = STATE+str(int(nHDs))+\"convexHD2_\"+str(int(nDistricts))+\"nW4_20Apr.csv\"  #solveWedgeC\n",
    "#outname = STATE+str(int(nTracts))+\"HD2Buutpatch\"+str(int(nDistricts))+\"nW4.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "HDdf.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "075013a3-f3ee-4a44-ac4a-27a7492e027a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "6e7e8ccd-8e11-4d6d-970d-b059401e0a3b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the original HD polygon shape assignment csv, e.g. ./2024state_HD_output/FL7211convexHD2_26nW4_03Mar.csv or ./state_HD_output/AZ9HD1tol0.005nW425Mar.csv ./2024state_HD_output/NJ6361convexHD2_12nW4_20Apr.csv\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I have read back in the original HD shapes\n",
      "Ready to capture unit centroids based on these HD poly shapes; see next block\n"
     ]
    }
   ],
   "source": [
    "#OPTION 2 --> 1 - we already have an ensemble of HDpoly's and their weights (from running option 2 above)\n",
    "#read them in\n",
    "#determine each cluster's required area fraction capture to get 1.00 cluster use across the HD set\n",
    "#then determine total pop (including cluster in/out) for each HD, and total unit use\n",
    "#then move into triage\n",
    "infilename = input(\"enter the original HD polygon shape assignment csv, \"+ \n",
    "                   \"e.g. ./2024state_HD_output/FL7211convexHD2_26nW4_03Mar.csv or ./state_HD_output/AZ9HD1tol0.005nW425Mar.csv\")\n",
    "shapeDF = pd.read_csv(infilename)\n",
    "HDvPop = shapeDF[\"HD-pop\"].to_list()\n",
    "HDweight = shapeDF['HDweight'].to_list() #shapeDF['HDwt'].to_list() or #shapeDF['HDweight'].to_list()\n",
    "HDarea = shapeDF['HDarea'].to_list()\n",
    "#tractPop = shapeDF['tractPop'].to_list()   #we will use vtd-mapped pops instead\n",
    "nHDs = len(shapeDF)\n",
    "hdCPx = shapeDF['centroid x'].to_list()   #note: these may be translated from outcroppings into a convex representation of the map\n",
    "hdCPy = shapeDF['centroid y'].to_list()\n",
    "hdCP = [Point(hdCPx[t], hdCPy[t]) for t in range(nHDs) ]\n",
    "HDradius0 = shapeDF['HDradius0'].to_list()\n",
    "HDradius1 = shapeDF['HDradius1'].to_list()\n",
    "HDradius2 = shapeDF['HDradius2'].to_list()\n",
    "HDradius3 = shapeDF['HDradius3'].to_list()\n",
    "HDangle0 = shapeDF['HDangle0'].to_list()\n",
    "HDangle1 = shapeDF['HDangle1'].to_list()\n",
    "HDangle2 = shapeDF['HDangle2'].to_list()\n",
    "HDangle3 = shapeDF['HDangle3'].to_list()\n",
    "HDradius, HDangle = list(), list()\n",
    "for t in range(nHDs):\n",
    "    HDradius.append( [HDradius0[t],HDradius1[t],HDradius2[t],HDradius3[t] ] )\n",
    "    HDangle.append(  [HDangle0[t], HDangle1[t], HDangle2[t], HDangle3[t]  ] )\n",
    "print(\"I have read back in the original HD shapes\")\n",
    "popHDlist = list()\n",
    "HDpoly = [dummyPoly for t in range(nHDs)]\n",
    "for t in range(nHDs):\n",
    "    if HDweight[t] > 0.000001:\n",
    "        popHDlist.append(t)\n",
    "        HDpoly[t] = buildArcPoly(hdCP[t],HDradius[t], HDangle[t], xScale)\n",
    "if \"countyNo\" in shapeDF.columns.values:  #\"pigs\" == \"can fly\":\n",
    "    HDcountyNo = shapeDF['countyNo'].to_list()\n",
    "else:\n",
    "    print(\"County numbers not in input file. Now I will assign each HD center to a county based on the county geoms\")\n",
    "    HDcountyNo = [-999]*nHDs\n",
    "    for t in popHDlist:\n",
    "        for c, geom in enumerate(countyGeom):\n",
    "            if geom.contains(hdCP[t]):\n",
    "                HDcountyNo[t] = c\n",
    "                break\n",
    "    unassignedList = list()\n",
    "    for t in popHDlist:\n",
    "        if HDcountyNo[t] == -999:\n",
    "            unassignedList.append(t)\n",
    "    if len(unassignedList) > 0:\n",
    "        print(\"I found\",len(unassignedList),\"populd HDs whose centers fall outside vtd-based county lines.  Assign to closest county\")\n",
    "        for t in unassignedList:\n",
    "            minDist = maxD\n",
    "            for c in range(nCounties):\n",
    "                dist = countyGeom[c].distance(hdCP[t])\n",
    "                if dist < minDist:\n",
    "                    minDist = dist\n",
    "                    HDcountyNo[t] = c\n",
    "    if len(unassignedList) > 0:\n",
    "        if len(unassignedList) > 20:\n",
    "            print(\"  (too many to plot individually)\")\n",
    "        else:\n",
    "            print(\"FYI, here are those manually assigned HDcenters to their counties\")\n",
    "            for t in unassignedList:\n",
    "                print(t,HDweight[t],\" is the HD row and its weight in the ensemble\")\n",
    "                plotPoly(hdCP[t].buffer(0.1))\n",
    "                plotCenter(int(HDvPop[t]),hdCP[t],6)\n",
    "                plotPoly(countyGeom[HDcountyNo[t]])\n",
    "                plotPoly(MAP,0.2)\n",
    "                plt.show()\n",
    "print(\"Ready to capture unit centroids based on these HD poly shapes; see next block\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "3f0f8434-5f7a-41d1-bd86-07ec230b4aef",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now, let me renormalize the HDweights if there were cut districts\n",
      "our HDweight sum was 0.9999999999997394 but is now 0.9999999999999998\n"
     ]
    }
   ],
   "source": [
    "print(\"now, let me renormalize the HDweights if there were cut districts\")\n",
    "sumWt = np.sum(HDweight)\n",
    "HDweight = [HDweight[t]/sumWt for t in range(nHDs) ]\n",
    "\n",
    "print(\"our HDweight sum was\",sumWt,\"but is now\",np.sum(HDweight))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "af22eba0-8e05-43e7-b96b-6aedab016957",
   "metadata": {},
   "outputs": [],
   "source": [
    "#see early states for continuing w/option 1.  NC and later use option 3 ....\n",
    "#if this is a cold restart, would need to read in unit topology before below block"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "8d5f678f-c2df-4ee7-bafe-fd75ba2cb42e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lead = 'option3' - create HDunitLists based on each HD's tractList, with in-out for multiVTD units\n"
     ]
    }
   ],
   "source": [
    "#OPTION 3 \n",
    "print(\"lead = 'option3' - create HDunitLists based on each HD's tractList, with in-out for multiVTD units\")\n",
    "HDtractListString = shapeDF[\"HDtractList\"]\n",
    "HDtractList = [ast.literal_eval(HDtractListString[t]) for t in range(nHDs)]\n",
    "nCCBs = len(CCBlist)\n",
    "CCBpopFrac = [[0. for j in range(nCCBs) ]  for t in range(nHDs)]\n",
    "\n",
    "unitParentVTDno = [-999 for u in range(nUnits)]\n",
    "for u in range(nUnits):    \n",
    "    if allUnits[u] %1 == 0:\n",
    "        v = allUnits[u]\n",
    "        unitParentVTDno[u] = parentVTDno[v]\n",
    "              "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "ec034144-b3dc-4b72-9350-6d85cabcb8a2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing option3, now assigning each HD's units (excluding CCB's) based on the captured whole vtd's\n",
      "working on vtd --> unit conversion for HD 1 last HD had pop 773034.0\n",
      "working on vtd --> unit conversion for HD 1001 last HD had pop 777410.0\n",
      "working on vtd --> unit conversion for HD 2001 last HD had pop 773771\n",
      "working on vtd --> unit conversion for HD 3001 last HD had pop 773131.0\n",
      "working on vtd --> unit conversion for HD 4001 last HD had pop 774510\n",
      "working on vtd --> unit conversion for HD 5001 last HD had pop 722492.0\n",
      "working on vtd --> unit conversion for HD 6001 last HD had pop 722534.0\n"
     ]
    }
   ],
   "source": [
    "print(\"Continuing option3, now assigning each HD's units (excluding CCB's) based on the captured whole vtd's\" )\n",
    "HDunitList = [ list() for t in range(nHDs) ]\n",
    "for t in range(nHDs):\n",
    "    if t %1000 == 1:\n",
    "        print(\"working on vtd --> unit conversion for HD\",t,\"last HD had pop\",r3( np.sum([unitPop[u] for u in HDunitList[t-1]]) ) )\n",
    "    capturedCountyPop = [0. for c in range(nCounties)]\n",
    "    capturedCCBpop = [0. for i in range(nCCBs)]\n",
    "    for v in HDtractList[t]:\n",
    "        c = HDcountyNo[v]\n",
    "        if c in range(nCounties):  #we assigned countyno = -999 to unpopulated tracts\n",
    "            if c in unitCounties:\n",
    "                capturedCountyPop[c] += tractPop[v]\n",
    "            elif c in allFusedCounties:\n",
    "                for i, L in enumerate(CCBlist):\n",
    "                    if c in L:\n",
    "                        capturedCCBpop[i] += tractPop[v]\n",
    "            else:  #this vtd not part of a unit or fused county.  Could be split into fragments\n",
    "                for u in countyUnitList[c]:\n",
    "                    if unitParentVTDno[u] == v :  #we assign all units = vtd fragments from this HDTL-captured vtd\n",
    "                        HDunitList[t].append(u)\n",
    "    for c in unitCounties:\n",
    "        if capturedCountyPop[c] > 0.5 * countyPop[c]:\n",
    "            HDunitList[t].append(allUnits.index(c+0.5))\n",
    "    for i in range(nCCBs):  #don't yet assign in/out CCBs.  We'll do so in below block\n",
    "        CCBpopFrac[t][i] = capturedCCBpop[i] / CCBpop[i]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "1494814c-7b90-425c-b8b1-3a2006bdeb2d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing option 3.  Determine each CCB's use if we add it to all adjoining HDs\n",
      "CCBno 0 with pop 95263.0 would be used 1.249 if we added it to all adjoining districts\n",
      "Here is the histogram of relative district pop with these added\n",
      "CCBno 1 with pop 64837.0 would be used 1.668 if we added it to all adjoining districts\n",
      "Here is the histogram of relative district pop with these added\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 if we are not allowed to use multiple CCB's in a single HD 0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CCBno 0 with pop 95263.0 would be used 1.2488198399094912 if we added it to all adjoining districts with no 2-CCB districts\n",
      "CCBno 1 with pop 64837.0 would be used 1.668382173570168 if we added it to all adjoining districts with no 2-CCB districts\n"
     ]
    }
   ],
   "source": [
    "print(\"Continuing option 3.  Determine each CCB's use if we add it to all adjoining HDs\")\n",
    "CCBwouldUse = [0. for i in range(nCCBs)]\n",
    "CCBaddCandidates = [list() for i in range(nCCBs)]\n",
    "for j in range(nCCBs):\n",
    "    jNo = allUnits.index(j+0.25)\n",
    "    ccbNbrSet = set(unitNbrs[jNo])\n",
    "    withCCBpopRat = list()\n",
    "    for t in range(nHDs):\n",
    "        if len(ccbNbrSet.intersection(set(HDunitList[t]))) > 0:\n",
    "            CCBwouldUse[j] += HDweight[t] * nDistricts\n",
    "            CCBaddCandidates[j].append(t)\n",
    "            withCCBpopRat.append((np.sum([unitPop[u] for u in HDunitList[t]]) + CCBpop[j]) / aDP )\n",
    "    print(\"CCBno\",j,\"with pop\",CCBpop[j],\"would be used\",r3(CCBwouldUse[j]),\"if we added it to all adjoining districts\")\n",
    "    print(\"Here is the histogram of relative district pop with these added\")\n",
    "    plt.hist(withCCBpopRat,histtype=\"step\",label=\"CCB \"+str(j))\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "avoidMultiCCBuse = int(input(\"enter 1 if we are not allowed to use multiple CCB's in a single HD\"))  #option by state\n",
    "if avoidMultiCCBuse == 1:\n",
    "    for j in range(nCCBs):  #this block -- preventing HDs from picking up multiple CCB's; instead, pick up the closest one  \n",
    "        jNo = allUnits.index(j+0.25)\n",
    "        for jj in range(j+1, nCCBs):\n",
    "            jjNo = allUnits.index(j+0.25)\n",
    "            for t in CCBaddCandidates[j].copy():\n",
    "                if t in CCBaddCandidates[j]:\n",
    "                    if t in CCBaddCandidates[jj].copy():\n",
    "                        dist_j, dist_jj = hdCP[t].distance(unitCP[jNo]), hdCP[t].distance(unitCP[jjNo])\n",
    "                        if dist_j > dist_jj:\n",
    "                            CCBaddCandidates[j].remove(t)  #for MN, don't allow any districts with two CCB's\n",
    "                            CCBwouldUse[j] -= HDweight[t] * nDistricts\n",
    "                        else:\n",
    "                            CCBaddCandidates[jj].remove(t)\n",
    "                            CCBwouldUse[jj] -= HDweight[t] * nDistricts\n",
    "for j in range(nCCBs):    \n",
    "    print(\"CCBno\",j,\"with pop\",CCBpop[j],\"would be used\",CCBwouldUse[j],\"if we added it to all adjoining districts with no 2-CCB districts\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "0d38eb0e-b516-4fd4-bb9e-6ca0eecfa772",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing option 3. Now assign CCB units.  For each, work from most to least underpopped\n",
      "final unit use of CCB 0 is 1.0003 ; here is a histogram of HDpop using this CCB\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final unit use of CCB 1 is 1.00038 ; here is a histogram of HDpop using this CCB\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Continuing option 3. Now assign CCB units.  For each, work from most to least underpopped\")\n",
    "#previously, we went from most-used to least-used CCB vtds until each has unit use\")\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "CCBuse = [0. for i in range(nCCBs)]\n",
    "for j in range(nCCBs):\n",
    "    postCCBaddPops = list()\n",
    "    unitNo = allUnits.index(j+0.25)\n",
    "    #ccbNbrSet = set(unitNbrs[unitNo])\n",
    "    #ccbFrac = [-1.*CCBpopFrac[t][j] for t in range(nHDs) ]  # -1 to go from most- to least-used\n",
    "    #idx = np.argsort(ccbFrac)\n",
    "    preCCBpop = [np.sum([unitPop[u] for u in HDunitList[t] ]) for t in CCBaddCandidates[j]]\n",
    "    idx = np.argsort(preCCBpop)\n",
    "    i = 0\n",
    "    t = CCBaddCandidates[j][idx[i]] #idx[i]\n",
    "    while CCBuse[j] < 1.00  and i < len(CCBaddCandidates[j]) :  #and CCBpopFrac[t][j] > 0:\n",
    "        t = CCBaddCandidates[j][idx[i]] #idx[i]\n",
    "        CCBuse[j] += HDweight[t] * nDistricts\n",
    "        HDunitList[t].append(unitNo)\n",
    "        postCCBaddPops.append(np.sum([unitPop[u] for u in HDunitList[t] ]))\n",
    "        i +=1\n",
    "    unitUse[unitNo] = CCBuse[j]\n",
    "    print(\"final unit use of CCB\",j, \"is\",r5(CCBuse[j]),\"; here is a histogram of HDpop using this CCB\")\n",
    "    plt.hist(postCCBaddPops)\n",
    "    plt.axvline(aDP,ls=\"--\")\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cf747d9c-cf6d-420e-9c3c-6723619586ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "#end of preliminaries for \"option 3\" - converting HDtractlists to unit lists instead of option 2's geometric probing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "26102ca2-79c1-48db-b873-7fa3a1553911",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "dc26d08c-a5d9-4e7e-9da5-ae98cf658a3a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here is the histogram of HD pops relative to aDP\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "orig unit avg and sd usage are 1.00295 0.10977\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t]]) for t in range(nHDs) ]\n",
    "print(\"Here is the histogram of HD pops relative to aDP\")\n",
    "plt.hist([HDvPop[t] / aDP for t in range(nHDs) ], bins=20, weights = HDweight, label= \"HDpop / target\" )\n",
    "plt.show()\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse, bins=50, weights=unitPop,label=\"read-in\",histtype=\"step\")\n",
    "plt.legend()\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "print(\"orig unit avg and sd usage are\",r5(unpatchedAvg), r5(unpatchedSD) )\n",
    "plt.show()\n",
    "currAvg, currSD = unpatchedAvg, unpatchedSD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "53e4c298-e6cb-4fee-a511-b8f6c3940539",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "c4183011-724a-4014-8c94-f9f9382c7e75",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Did I grossly overuse any units, or skip any live ones?\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "above: underused < 0.5; below overused > 1.6\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Did I grossly overuse any units, or skip any live ones?\")\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < 0.5 and unitPop[u] > 5:\n",
    "        plotPoly(unitGeom[u])\n",
    "        #print(u,unitPop[u], unitUse[u])\n",
    "        #for c in range(nCounties):\n",
    "        #    if u in countyUnitList[c]:\n",
    "        #        print(u,\"is in county\",c)\n",
    "        #        print(\"its neighbor units are\",unitNbrs[u])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()\n",
    "print(\"above: underused < 0.5; below overused > 1.6\")\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 1.6:\n",
    "        plotPoly(unitGeom[u],0.3)\n",
    "plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "ce9292b0-7d6a-419a-9491-d0def779ad04",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are a total of 6356 populated HDs out of 6361\n"
     ]
    }
   ],
   "source": [
    "popHDlist = list()\n",
    "for t in range(nHDs):\n",
    "    if len(HDunitList[t]) > 0:\n",
    "        popHDlist.append(t)\n",
    "populatedTractList = popHDlist.copy()\n",
    "print(\"there are a total of\",len(populatedTractList),\"populated HDs out of\",nHDs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "f7f36559-7f1d-4203-8b24-0e8cc2ce1753",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this will show if we had any duplicated units in HDunitLists\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"this will show if we had any duplicated units in HDunitLists\")\n",
    "excess = [0 for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    excess[t] = len(HDunitList[t]) - len(set(HDunitList[t]))\n",
    "plt.hist(excess)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "27bc7f0a-d7ff-4c68-830f-29ba5013c314",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#popHDlist = populatedTractList.copy()  #somehow our popHDlist started to include the cut District HD starters\n",
    "HDunitList = [list(set(HDunitList[t])) for t in range(nHDs)]\n",
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t]]) for t in range(nHDs)]\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP,ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "af8a4945-40c2-40df-8dd4-d516f4de2f0f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "quick classification: who has contiguity problems?\n",
      "working on HD 0 time is now 0\n",
      "working on HD 700 time is now 97\n",
      "working on HD 1401 time is now 161\n",
      "working on HD 2103 time is now 219\n",
      "working on HD 2803 time is now 297\n",
      "working on HD 3503 time is now 368\n",
      "working on HD 4203 time is now 468\n",
      "working on HD 4903 time is now 544\n",
      "working on HD 5604 time is now 624\n",
      "working on HD 6305 time is now 695\n",
      "out of 6356 total HDs, there were 5005.0 contiguous and 938.0 complement-contiguous HDs\n",
      "1146 HDs had both discontiguity problems, while enclave-only = 4272 and discontig only= 205\n",
      "here are the histograms of the small piece and enclave list lengths, total no = 1351 4272\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "And here are the small-HD-piece and small-enclave pops\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### THIS IS THE \"FIND DISCO\" CODE\n",
    "print(\"quick classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%700 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs,4) #,6) #6 is high (slow) to try to avoid false enclaves\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )\n",
    "\n",
    "print(\"here are the histograms of the small piece and enclave list lengths, total no =\",\n",
    "      len(smallPieceLists),len(enclaveLists) )\n",
    "plt.hist([s for s in smallPieceLengths],label=\"small piece l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "plt.hist([e for e in enclaveLengths],label=\"enclave l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "plt.legend()\n",
    "plt.show()\n",
    "print(\"And here are the small-HD-piece and small-enclave pops\")\n",
    "plt.hist([sum(unitPop[u] for u in s) for s in smallPieceLists],label=\"small piece 1 pop\",histtype='step')\n",
    "plt.hist([sum(unitPop[u] for u in e) for e in enclaveLists],label=\"enclave 1 pop\",histtype='step')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "40f06e44-45be-4a36-b62c-26698af70e06",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Before addressing enclaves, let's triage the discontinuous HDs\n",
      "Now work on dropping smallish disconnected pieces that would keep us above 735378 district pop vs 774082 target\n",
      "we'll also trim any HD with total islands' pop <= 15481\n",
      "working on HD 13\n",
      "working on HD 908\n",
      "working on HD 1500\n",
      "working on HD 2657\n",
      "working on HD 4027\n",
      "working on HD 4913\n",
      "working on HD 5491\n",
      "Out of 1351 discontig HDs 1351 had discontig HDs.\n",
      "Of these, 836 won't be under 735378 after all minor discontigys were shed, while 515 would be too underpopped if we trimmed the discontig pieces\n",
      "here is adjusted pop by original pop for those we trimmed and those we didn't (x)\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, reclassify after the trimming\n",
      "reclassifying HD 13\n",
      "reclassifying HD 2007\n",
      "reclassifying HD 4913\n",
      "There are 515 HDs still with both discontinuity problems\n",
      "Additionally, 695 of the originally discontig HDs are now contig but still have an enclave\n"
     ]
    }
   ],
   "source": [
    "print(\"Before addressing enclaves, let's triage the discontinuous HDs\")\n",
    "#this is the CANTRIM code####\n",
    "\n",
    "#for t in sPgenerator:\n",
    "#    isContig, smallP = isContiguous(filledHDvtdList[t],unitNbrs)\n",
    "#    if isContig:\n",
    "#        print(\"oops!\",t)\n",
    "maxNudgeDownPop = int(0.02 * aDP)\n",
    "minPostFixPop = int(0.95 * aDP)\n",
    "print(\"Now work on dropping smallish disconnected pieces that would keep us above\",minPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "print(\"we'll also trim any HD with total islands' pop <=\",maxNudgeDownPop)\n",
    "nOrigIslands = [0 for t in range(nHDs)]\n",
    "totalIslandPop = [0. for t in range(nHDs)]\n",
    "tryToTrim, canTrim, cantTrim = list(), list(), list()\n",
    "for jj, t in enumerate(sPgenerator):\n",
    "    if jj%200 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    currList, shedList, shedPop = HDunitList[t].copy(), list(),  0.\n",
    "    done,newList = isContiguous(currList,unitNbrs)\n",
    "    if not done:\n",
    "        tryToTrim.append(t)\n",
    "        while not done:\n",
    "            shedList += newList\n",
    "            shedPop += np.sum( [unitPop[u] for u in newList] )\n",
    "            currList = list (  set(currList).difference(set(newList ))  )\n",
    "            done, newList = isContiguous(currList, unitNbrs)\n",
    "            nOrigIslands[t] +=1\n",
    "            \n",
    "        totalIslandPop[t] = shedPop            \n",
    "        if shedPop <= maxNudgeDownPop or HDvPop[t] - shedPop >= minPostFixPop:\n",
    "            canTrim.append(t)\n",
    "            HDvPop[t] -= shedPop\n",
    "            HDunitList[t] = list (set(HDunitList[t]).difference(set(shedList)) )\n",
    "        else:\n",
    "            cantTrim.append(t)\n",
    "print(\"Out of\",len(sPgenerator),\"discontig HDs\",len(tryToTrim),\"had discontig HDs.\")\n",
    "print(\"Of these,\",len(canTrim),\"won't be under\",minPostFixPop,\"after all minor discontigys were shed, while\",\n",
    "      len(cantTrim),\"would be too underpopped if we trimmed the discontig pieces\")\n",
    "plt.scatter([HDvPop[t] + totalIslandPop[t] for t in canTrim],[HDvPop[t] for t in canTrim])\n",
    "plt.scatter([HDvPop[t]                     for t in cantTrim],[HDvPop[t] for t in cantTrim],marker=\"x\")\n",
    "print(\"here is adjusted pop by original pop for those we trimmed and those we didn't (x)\")\n",
    "plt.plot([0.9*aDP, 1.1*aDP],[aDP, aDP], ls=\"--\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Now, reclassify after the trimming\")\n",
    "badDiscoList, stillHasEnclave = list(), list()\n",
    "for i, t in enumerate(sPgenerator):    \n",
    "    if i%500 == 0:\n",
    "        print(\"reclassifying HD\",t)\n",
    "    unbroken, noEnclave, __, ____ = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if not unbroken:\n",
    "        badDiscoList.append(t)  #will do a major triage on these later\n",
    "    if unbroken and not noEnclave:\n",
    "        stillHasEnclave.append(t)\n",
    "print(\"There are\",len(badDiscoList),\"HDs still with both discontinuity problems\")\n",
    "print(\"Additionally,\",len(stillHasEnclave),\"of the originally discontig HDs are now contig but still have an enclave\")\n",
    "eLgenerator += stillHasEnclave"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "4037f8cb-661b-4032-bfb9-e147975e3bbb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/13/24 - classify further: ID those with adjoiners intersecting the map boundary vs internal islands\n",
      "working on enclave-generating HD 0\n",
      "working on enclave-generating HD 630\n",
      "working on enclave-generating HD 1532\n",
      "working on enclave-generating HD 2421\n",
      "working on enclave-generating HD 3091\n",
      "working on enclave-generating HD 3753\n",
      "working on enclave-generating HD 4336\n",
      "working on enclave-generating HD 5103\n",
      "working on enclave-generating HD 5914\n",
      "working on enclave-generating HD 2142\n",
      "Out of 4967 HDpolys that generated enclaves, 0 had contiguous adjrs, while 4000 neighbored a state boundary while 967 had only internal enclaves\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 to print the total enclave pops for all enclavy HDs.  This takes a few min; not required 0\n"
     ]
    }
   ],
   "source": [
    "print(\"1/13/24 - classify further: ID those with adjoiners intersecting the map boundary vs internal islands\")\n",
    "internals, edgers, nOK = list(), list(), 0\n",
    "for i,t in enumerate(eLgenerator):\n",
    "    if i%500 == 0:\n",
    "        print(\"working on enclave-generating HD\",t)\n",
    "    twoNbrs = get2nbrs(HDunitList[t],unitNbrs)\n",
    "    isContig, adjSublist = isContiguous(twoNbrs,unitNbrs)\n",
    "    if isContig:\n",
    "        nOK +=1\n",
    "    else:\n",
    "        if len (set(getAdjoiners(HDunitList[t],unitNbrs)).intersection(set(borderUnits)))  > 0:\n",
    "            edgers.append(t)\n",
    "        else:\n",
    "            internals.append(t)\n",
    "print(\"Out of\",len(eLgenerator),\"HDpolys that generated enclaves,\",nOK,\"had contiguous adjrs, while\",len(edgers),\n",
    "      \"neighbored a state boundary while\",len(internals),\"had only internal enclaves\")\n",
    " \n",
    "plotEnclaves = input(\"enter 1 to print the total enclave pops for all enclavy HDs.  This takes a few min; not required\")\n",
    "if str(plotEnclaves) == str(1):\n",
    "    for i,t in enumerate(internals): \n",
    "        if i%500 == 0:\n",
    "            print(\"computing full enclave lists for HD\",t)\n",
    "        fullEnclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "        tEpop = np.sum( [ [np.sum([unitPop[u] for u in eL])] for eL in fullEnclaveLists ] ) \n",
    "        plt.scatter(HDvPop[t],tEpop)\n",
    "    plt.plot([aDP,aDP],[0,5000],ls=\"--\")\n",
    "    print(\"Here are the total enclave pops for enclaving HDs not touching the state boundary vs. the original HD pop\")\n",
    "    plt.show()    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "05f929ce-4f94-47a6-baf4-60c5a89e2ae5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, let's fill in all enclaves that won't put us over 812786 district pop vs 774082 target\n",
      "working on enclave-y HD 2 . We have evaluated 0 of 4967 enclavy HDs.Time is now 0\n",
      "working on enclave-y HD 445 . We have evaluated 100 of 4967 enclavy HDs.Time is now 18\n",
      "working on enclave-y HD 1771 . We have evaluated 200 of 4967 enclavy HDs.Time is now 37\n",
      "working on enclave-y HD 2683 . We have evaluated 300 of 4967 enclavy HDs.Time is now 56\n",
      "working on enclave-y HD 3279 . We have evaluated 400 of 4967 enclavy HDs.Time is now 73\n",
      "working on enclave-y HD 3490 . We have evaluated 500 of 4967 enclavy HDs.Time is now 89\n",
      "working on enclave-y HD 3786 . We have evaluated 600 of 4967 enclavy HDs.Time is now 105\n",
      "working on enclave-y HD 3962 . We have evaluated 700 of 4967 enclavy HDs.Time is now 123\n",
      "working on enclave-y HD 4108 . We have evaluated 800 of 4967 enclavy HDs.Time is now 141\n",
      "working on enclave-y HD 39 . We have evaluated 900 of 4967 enclavy HDs.Time is now 158\n",
      "working on enclave-y HD 55 . We have evaluated 1000 of 4967 enclavy HDs.Time is now 173\n",
      "working on enclave-y HD 236 . We have evaluated 1100 of 4967 enclavy HDs.Time is now 187\n",
      "working on enclave-y HD 414 . We have evaluated 1200 of 4967 enclavy HDs.Time is now 202\n",
      "working on enclave-y HD 604 . We have evaluated 1300 of 4967 enclavy HDs.Time is now 217\n",
      "working on enclave-y HD 807 . We have evaluated 1400 of 4967 enclavy HDs.Time is now 228\n",
      "working on enclave-y HD 1020 . We have evaluated 1500 of 4967 enclavy HDs.Time is now 237\n",
      "working on enclave-y HD 1231 . We have evaluated 1600 of 4967 enclavy HDs.Time is now 247\n",
      "working on enclave-y HD 1407 . We have evaluated 1700 of 4967 enclavy HDs.Time is now 261\n",
      "working on enclave-y HD 1609 . We have evaluated 1800 of 4967 enclavy HDs.Time is now 275\n",
      "working on enclave-y HD 1788 . We have evaluated 1900 of 4967 enclavy HDs.Time is now 287\n",
      "working on enclave-y HD 2039 . We have evaluated 2000 of 4967 enclavy HDs.Time is now 309\n",
      "working on enclave-y HD 2180 . We have evaluated 2100 of 4967 enclavy HDs.Time is now 336\n",
      "working on enclave-y HD 2330 . We have evaluated 2200 of 4967 enclavy HDs.Time is now 358\n",
      "working on enclave-y HD 2531 . We have evaluated 2300 of 4967 enclavy HDs.Time is now 371\n",
      "working on enclave-y HD 2723 . We have evaluated 2400 of 4967 enclavy HDs.Time is now 383\n",
      "working on enclave-y HD 2888 . We have evaluated 2500 of 4967 enclavy HDs.Time is now 401\n",
      "working on enclave-y HD 3052 . We have evaluated 2600 of 4967 enclavy HDs.Time is now 409\n",
      "working on enclave-y HD 3250 . We have evaluated 2700 of 4967 enclavy HDs.Time is now 418\n",
      "working on enclave-y HD 3551 . We have evaluated 2800 of 4967 enclavy HDs.Time is now 430\n",
      "working on enclave-y HD 3795 . We have evaluated 2900 of 4967 enclavy HDs.Time is now 447\n",
      "working on enclave-y HD 4133 . We have evaluated 3000 of 4967 enclavy HDs.Time is now 461\n",
      "working on enclave-y HD 4296 . We have evaluated 3100 of 4967 enclavy HDs.Time is now 476\n",
      "working on enclave-y HD 4441 . We have evaluated 3200 of 4967 enclavy HDs.Time is now 487\n",
      "working on enclave-y HD 4609 . We have evaluated 3300 of 4967 enclavy HDs.Time is now 500\n",
      "working on enclave-y HD 4775 . We have evaluated 3400 of 4967 enclavy HDs.Time is now 515\n",
      "working on enclave-y HD 4947 . We have evaluated 3500 of 4967 enclavy HDs.Time is now 528\n",
      "working on enclave-y HD 5120 . We have evaluated 3600 of 4967 enclavy HDs.Time is now 544\n",
      "working on enclave-y HD 5321 . We have evaluated 3700 of 4967 enclavy HDs.Time is now 558\n",
      "working on enclave-y HD 5527 . We have evaluated 3800 of 4967 enclavy HDs.Time is now 572\n",
      "working on enclave-y HD 5666 . We have evaluated 3900 of 4967 enclavy HDs.Time is now 589\n",
      "working on enclave-y HD 5816 . We have evaluated 4000 of 4967 enclavy HDs.Time is now 610\n",
      "working on enclave-y HD 5951 . We have evaluated 4100 of 4967 enclavy HDs.Time is now 624\n",
      "working on enclave-y HD 6103 . We have evaluated 4200 of 4967 enclavy HDs.Time is now 632\n",
      "working on enclave-y HD 6253 . We have evaluated 4300 of 4967 enclavy HDs.Time is now 646\n",
      "working on enclave-y HD 699 . We have evaluated 4400 of 4967 enclavy HDs.Time is now 658\n",
      "working on enclave-y HD 1426 . We have evaluated 4500 of 4967 enclavy HDs.Time is now 672\n",
      "working on enclave-y HD 2826 . We have evaluated 4600 of 4967 enclavy HDs.Time is now 689\n",
      "working on enclave-y HD 4194 . We have evaluated 4700 of 4967 enclavy HDs.Time is now 701\n",
      "working on enclave-y HD 4946 . We have evaluated 4800 of 4967 enclavy HDs.Time is now 714\n",
      "working on enclave-y HD 5660 . We have evaluated 4900 of 4967 enclavy HDs.Time is now 730\n",
      "Out of 4967 HDs with enclaves 4967 had enclaves.\n",
      "Of these, 4789 wouldn't be over 812786 if all enclaves filled, while 178 were too populous\n",
      "here is enclave pop by final pop for those we filled\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### THIS IS THE \"CANFILL\" CODE  #check if sum of enclave pops small enough to add\n",
    "maxNudgeUpPop = int(0.02 * aDP)\n",
    "maxPostFixPop = int(1.05 * aDP)\n",
    "print(\"Now, let's fill in all enclaves that won't put us over\",maxPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "nOrigEnclaves = [0 for t in range(nHDs)]\n",
    "totalEnclavePop = [0. for t in range(nHDs)]\n",
    "tryToFill, canFill, cantFill = list(), list(), list()\n",
    "startTime = time.time()  #takes about xx sec per HD triage\n",
    "        \n",
    "for iii, t in enumerate(internals + edgers):\n",
    "    if iii%100 == 0:\n",
    "        print(\"working on enclave-y HD\",t,\". We have evaluated\",iii,\"of\",len(internals+edgers),\"enclavy HDs.Time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and not noEnclave:  #\"and unbroken\" new 1/15 - discontig HDs will usually appear to have enclaves.  We'll fix these in later block\n",
    "        tryToFill.append(t)\n",
    "        enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "        nOrigEnclaves[t] = len(enclaveLists)\n",
    "        totalEnclavePop[t] = np.sum( [ [np.sum([unitPop[u] for u in eL])] for eL in enclaveLists ] ) \n",
    "        if HDvPop[t] + totalEnclavePop[t] <= maxPostFixPop or totalEnclavePop[t] < maxNudgeUpPop:\n",
    "            canFill.append(t)\n",
    "            for eL in enclaveLists:\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += np.sum([unitPop[u] for u in eL])\n",
    "        else:\n",
    "            cantFill.append(t)\n",
    "print(\"Out of\",len(internals+edgers),\"HDs with enclaves\",len(tryToFill),\"had enclaves.\")\n",
    "print(\"Of these,\",len(canFill),\"wouldn't be over\",maxPostFixPop,\"if all enclaves filled, while\",len(cantFill),\"were too populous\")\n",
    "plt.scatter([HDvPop[t] for t in canFill],[totalEnclavePop[t] for t in canFill])\n",
    "print(\"here is enclave pop by final pop for those we filled\")\n",
    "plt.show()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "8987ad1f-d372-415d-a2ec-8fc6736c5102",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "967 4000 1146 627\n",
      "178 178 4789\n"
     ]
    }
   ],
   "source": [
    "print(len(internals),len(edgers),len(doubleTroubleList),len(set(edgers).intersection(set(doubleTroubleList))))\n",
    "print(len(set(edgers).difference(set(canFill))) ,len(cantFill) , len(canFill))\n",
    "#610 3379 2187 1954\n",
    "#80 80 3909  for original MN option3 (assigned CCBs by captured area)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "8fa887be-92e6-422a-8e80-e00fd3265aab",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "defining and displaying current unit use after above manipulations; compare to original farther above.\n",
      "current avg use and its sd are 1.00437 0.10951\n",
      "CCB cluster 0 = unit 6197 with pop 95263.0 now has use of 1.0002973411329803\n",
      "CCB cluster 1 = unit 6198 with pop 64837.0 now has use of 0.9982342544305851\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"defining and displaying current unit use after above manipulations; compare to original farther above.\")\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "for u, unitNo in enumerate(allUnits):\n",
    "    if unitNo % 1 == 0.25:\n",
    "        print(\"CCB cluster\",int(unitNo),\"= unit\",u,\"with pop\",unitPop[u],\"now has use of\",unitUse[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "e9d50ef8-39b2-4e22-a11e-cabeda78721e",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "savedHDunitList = [HDunitList[t].copy() for t in range(nHDs) ]  #safekeeping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "b759b3c7-b8a3-4d2c-a8fe-50fa93b3e940",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjAAAAGdCAYAAAAMm0nCAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/H5lhTAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAyw0lEQVR4nO3de3RU5b3/8U9IyJAAM+FiMkQCRGmBQACJGsYqRyVlwNjaY1wVpUAravEETyEWQlYp3k4bilqkitDWauwqlMs5QiupYAgFVAJqauQmqVI0eGASj5gMICQheX5/+MsuA+ESSJo88f1aa6/F7P3dzzz7u2Ln0z177wkzxhgBAABYpENrTwAAAKCpCDAAAMA6BBgAAGAdAgwAALAOAQYAAFiHAAMAAKxDgAEAANYhwAAAAOtEtPYEWkp9fb0OHjyorl27KiwsrLWnAwAALoAxRkeOHFF8fLw6dDj7eZZ2G2AOHjyohISE1p4GAAC4CAcOHFDv3r3Pur3dBpiuXbtK+rIBbre7lWcDAAAuRDAYVEJCgvM5fjbtNsA0fG3kdrsJMAAAWOZ8l39wES8AALAOAQYAAFiHAAMAAKxDgAEAANYhwAAAAOsQYAAAgHUIMAAAwDoEGAAAYB0CDAAAsA4BBgAAWIcAAwAArEOAAQAA1iHAAAAA6xBgAACAdSJaewIALky/2fktNvZH89JbbGwAaAmcgQEAANYhwAAAAOsQYAAAgHUIMAAAwDoEGAAAYB0CDAAAsA4BBgAAWIcAAwAArEOAAQAA1rmkADNv3jyFhYVp+vTpzroTJ04oMzNTPXr0UJcuXZSRkaHy8vKQ/crKypSenq7o6GjFxsZq5syZOnnyZEjNpk2bNGLECLlcLvXv3195eXmXMlUAANCOXHSAefvtt/XrX/9aQ4cODVk/Y8YMvfLKK1q1apU2b96sgwcP6vbbb3e219XVKT09XTU1Ndq6dateeukl5eXlae7cuU7N/v37lZ6erptuukklJSWaPn267r33Xq1fv/5ipwsAANqRiwowR48e1YQJE/Tb3/5W3bp1c9ZXVVXpd7/7nX75y1/q5ptvVkpKil588UVt3bpV27ZtkyS99tpr2rNnj/7whz9o+PDhGjdunB5//HEtWrRINTU1kqQlS5YoMTFRTz31lAYNGqRp06bpjjvu0IIFC5rhkAEAgO0uKsBkZmYqPT1daWlpIeuLi4tVW1sbsn7gwIHq06ePioqKJElFRUVKTk5WXFycU+P3+xUMBrV7926n5vSx/X6/M0ZjqqurFQwGQxYAANA+NfnXqJcvX66//e1vevvtt8/YFggEFBkZqZiYmJD1cXFxCgQCTs2p4aVhe8O2c9UEg0EdP35cUVFRZ7x3bm6uHn300aYeDgAAsFCTzsAcOHBAP/rRj7R06VJ16tSppeZ0UXJyclRVVeUsBw4caO0pAQCAFtKkAFNcXKyKigqNGDFCERERioiI0ObNm/WrX/1KERERiouLU01NjSorK0P2Ky8vl9frlSR5vd4z7kpqeH2+Grfb3ejZF0lyuVxyu90hCwAAaJ+aFGBGjx6tnTt3qqSkxFmuvvpqTZgwwfl3x44dVVhY6OxTWlqqsrIy+Xw+SZLP59POnTtVUVHh1BQUFMjtdispKcmpOXWMhpqGMQAAwFdbk66B6dq1q4YMGRKyrnPnzurRo4ezfsqUKcrKylL37t3ldrv14IMPyufzaeTIkZKkMWPGKCkpSRMnTtT8+fMVCAQ0Z84cZWZmyuVySZKmTp2qZ599VrNmzdI999yjjRs3auXKlcrPz2+OYwYAAJZr8kW857NgwQJ16NBBGRkZqq6ult/v13PPPedsDw8P19q1a/XAAw/I5/Opc+fOmjx5sh577DGnJjExUfn5+ZoxY4YWLlyo3r176/nnn5ff72/u6QIAAAuFGWNMa0+iJQSDQXk8HlVVVXE9DNqFfrNb7gzkR/PSW2xsAGiKC/385reQAACAdQgwAADAOgQYAABgHQIMAACwDgEGAABYhwADAACsQ4ABAADWIcAAAADrEGAAAIB1CDAAAMA6BBgAAGAdAgwAALAOAQYAAFiHAAMAAKxDgAEAANYhwAAAAOsQYAAAgHUIMAAAwDoEGAAAYB0CDAAAsA4BBgAAWIcAAwAArEOAAQAA1iHAAAAA6xBgAACAdQgwAADAOgQYAABgHQIMAACwDgEGAABYhwADAACsQ4ABAADWaVKAWbx4sYYOHSq32y232y2fz6dXX33V2X7jjTcqLCwsZJk6dWrIGGVlZUpPT1d0dLRiY2M1c+ZMnTx5MqRm06ZNGjFihFwul/r376+8vLyLP0IAANDuRDSluHfv3po3b56+9rWvyRijl156SbfddpveffddDR48WJJ033336bHHHnP2iY6Odv5dV1en9PR0eb1ebd26VYcOHdKkSZPUsWNH/fznP5ck7d+/X+np6Zo6daqWLl2qwsJC3XvvverVq5f8fn9zHDMAALBcmDHGXMoA3bt31xNPPKEpU6boxhtv1PDhw/X00083Wvvqq6/q1ltv1cGDBxUXFydJWrJkibKzs/Xpp58qMjJS2dnZys/P165du5z9xo8fr8rKSq1bt+6C5xUMBuXxeFRVVSW3230phwi0Cf1m57fY2B/NS2+xsQGgKS708/uir4Gpq6vT8uXLdezYMfl8Pmf90qVL1bNnTw0ZMkQ5OTn64osvnG1FRUVKTk52wosk+f1+BYNB7d6926lJS0sLeS+/36+ioqJzzqe6ulrBYDBkAQAA7VOTvkKSpJ07d8rn8+nEiRPq0qWLVq9eraSkJEnS3Xffrb59+yo+Pl47duxQdna2SktL9fLLL0uSAoFASHiR5LwOBALnrAkGgzp+/LiioqIanVdubq4effTRph4OAACwUJMDzIABA1RSUqKqqir993//tyZPnqzNmzcrKSlJ999/v1OXnJysXr16afTo0dq3b5+uvPLKZp346XJycpSVleW8DgaDSkhIaNH3BAAAraPJXyFFRkaqf//+SklJUW5uroYNG6aFCxc2WpuamipJ+vDDDyVJXq9X5eXlITUNr71e7zlr3G73Wc++SJLL5XLujmpYAABA+3TJz4Gpr69XdXV1o9tKSkokSb169ZIk+Xw+7dy5UxUVFU5NQUGB3G638zWUz+dTYWFhyDgFBQUh19kAAICvtiZ9hZSTk6Nx48apT58+OnLkiJYtW6ZNmzZp/fr12rdvn5YtW6ZbbrlFPXr00I4dOzRjxgyNGjVKQ4cOlSSNGTNGSUlJmjhxoubPn69AIKA5c+YoMzNTLpdLkjR16lQ9++yzmjVrlu655x5t3LhRK1euVH5+y92BAQAA7NKkAFNRUaFJkybp0KFD8ng8Gjp0qNavX69vfvObOnDggDZs2KCnn35ax44dU0JCgjIyMjRnzhxn//DwcK1du1YPPPCAfD6fOnfurMmTJ4c8NyYxMVH5+fmaMWOGFi5cqN69e+v555/nGTAAAMBxyc+Baat4DgzaG54DA+CroMWfAwMAANBaCDAAAMA6BBgAAGAdAgwAALAOAQYAAFiHAAMAAKxDgAEAANYhwAAAAOsQYAAAgHUIMAAAwDoEGAAAYB0CDAAAsA4BBgAAWIcAAwAArEOAAQAA1iHAAAAA6xBgAACAdQgwAADAOgQYAABgHQIMAACwDgEGAABYhwADAACsQ4ABAADWIcAAAADrEGAAAIB1CDAAAMA6BBgAAGAdAgwAALAOAQYAAFiHAAMAAKxDgAEAANZpUoBZvHixhg4dKrfbLbfbLZ/Pp1dffdXZfuLECWVmZqpHjx7q0qWLMjIyVF5eHjJGWVmZ0tPTFR0drdjYWM2cOVMnT54Mqdm0aZNGjBghl8ul/v37Ky8v7+KPEAAAtDtNCjC9e/fWvHnzVFxcrHfeeUc333yzbrvtNu3evVuSNGPGDL3yyitatWqVNm/erIMHD+r222939q+rq1N6erpqamq0detWvfTSS8rLy9PcuXOdmv379ys9PV033XSTSkpKNH36dN17771av359Mx0yAACwXZgxxlzKAN27d9cTTzyhO+64Q5dddpmWLVumO+64Q5K0d+9eDRo0SEVFRRo5cqReffVV3XrrrTp48KDi4uIkSUuWLFF2drY+/fRTRUZGKjs7W/n5+dq1a5fzHuPHj1dlZaXWrVt3wfMKBoPyeDyqqqqS2+2+lEME2oR+s/NbbOyP5qW32NgA0BQX+vl90dfA1NXVafny5Tp27Jh8Pp+Ki4tVW1urtLQ0p2bgwIHq06ePioqKJElFRUVKTk52wosk+f1+BYNB5yxOUVFRyBgNNQ1jnE11dbWCwWDIAgAA2qcmB5idO3eqS5cucrlcmjp1qlavXq2kpCQFAgFFRkYqJiYmpD4uLk6BQECSFAgEQsJLw/aGbeeqCQaDOn78+FnnlZubK4/H4ywJCQlNPTQAAGCJJgeYAQMGqKSkRNu3b9cDDzygyZMna8+ePS0xtybJyclRVVWVsxw4cKC1pwQAAFpIRFN3iIyMVP/+/SVJKSkpevvtt7Vw4ULdeeedqqmpUWVlZchZmPLycnm9XkmS1+vVW2+9FTJew11Kp9acfudSeXm53G63oqKizjovl8sll8vV1MMBAAAWuuTnwNTX16u6ulopKSnq2LGjCgsLnW2lpaUqKyuTz+eTJPl8Pu3cuVMVFRVOTUFBgdxut5KSkpyaU8doqGkYAwAAoElnYHJycjRu3Dj16dNHR44c0bJly7Rp0yatX79eHo9HU6ZMUVZWlrp37y63260HH3xQPp9PI0eOlCSNGTNGSUlJmjhxoubPn69AIKA5c+YoMzPTOXsydepUPfvss5o1a5buuecebdy4UStXrlR+fsvdgQEAAOzSpABTUVGhSZMm6dChQ/J4PBo6dKjWr1+vb37zm5KkBQsWqEOHDsrIyFB1dbX8fr+ee+45Z//w8HCtXbtWDzzwgHw+nzp37qzJkyfrsccec2oSExOVn5+vGTNmaOHCherdu7eef/55+f3+ZjpkAABgu0t+DkxbxXNg0N7wHBgAXwUt/hwYAACA1kKAAQAA1iHAAAAA6xBgAACAdQgwAADAOgQYAABgHQIMAACwDgEGAABYhwADAACsQ4ABAADWIcAAAADrEGAAAIB1CDAAAMA6BBgAAGAdAgwAALAOAQYAAFiHAAMAAKxDgAEAANYhwAAAAOsQYAAAgHUIMAAAwDoEGAAAYB0CDAAAsA4BBgAAWIcAAwAArEOAAQAA1iHAAAAA6xBgAACAdQgwAADAOgQYAABgHQIMAACwDgEGAABYp0kBJjc3V9dcc426du2q2NhYfec731FpaWlIzY033qiwsLCQZerUqSE1ZWVlSk9PV3R0tGJjYzVz5kydPHkypGbTpk0aMWKEXC6X+vfvr7y8vIs7QgAA0O40KcBs3rxZmZmZ2rZtmwoKClRbW6sxY8bo2LFjIXX33XefDh065Czz5893ttXV1Sk9PV01NTXaunWrXnrpJeXl5Wnu3LlOzf79+5Wenq6bbrpJJSUlmj59uu69916tX7/+Eg8XAAC0BxFNKV63bl3I67y8PMXGxqq4uFijRo1y1kdHR8vr9TY6xmuvvaY9e/Zow4YNiouL0/Dhw/X4448rOztbjzzyiCIjI7VkyRIlJibqqaeekiQNGjRIb7zxhhYsWCC/39/UYwQAAO3MJV0DU1VVJUnq3r17yPqlS5eqZ8+eGjJkiHJycvTFF18424qKipScnKy4uDhnnd/vVzAY1O7du52atLS0kDH9fr+KiorOOpfq6moFg8GQBQAAtE9NOgNzqvr6ek2fPl3f+MY3NGTIEGf93Xffrb59+yo+Pl47duxQdna2SktL9fLLL0uSAoFASHiR5LwOBALnrAkGgzp+/LiioqLOmE9ubq4effTRiz0cAABgkYsOMJmZmdq1a5feeOONkPX333+/8+/k5GT16tVLo0eP1r59+3TllVde/EzPIycnR1lZWc7rYDCohISEFns/AADQei7qK6Rp06Zp7dq1+utf/6revXufszY1NVWS9OGHH0qSvF6vysvLQ2oaXjdcN3O2Grfb3ejZF0lyuVxyu90hCwAAaJ+aFGCMMZo2bZpWr16tjRs3KjEx8bz7lJSUSJJ69eolSfL5fNq5c6cqKiqcmoKCArndbiUlJTk1hYWFIeMUFBTI5/M1ZboAAKCdalKAyczM1B/+8ActW7ZMXbt2VSAQUCAQ0PHjxyVJ+/bt0+OPP67i4mJ99NFH+vOf/6xJkyZp1KhRGjp0qCRpzJgxSkpK0sSJE/Xee+9p/fr1mjNnjjIzM+VyuSRJU6dO1T/+8Q/NmjVLe/fu1XPPPaeVK1dqxowZzXz4AADARk0KMIsXL1ZVVZVuvPFG9erVy1lWrFghSYqMjNSGDRs0ZswYDRw4UA899JAyMjL0yiuvOGOEh4dr7dq1Cg8Pl8/n0/e+9z1NmjRJjz32mFOTmJio/Px8FRQUaNiwYXrqqaf0/PPPcws1AACQJIUZY0xrT6IlBINBeTweVVVVcT0M2oV+s/NbbOyP5qW32NgA0BQX+vnNbyEBAADrEGAAAIB1CDAAAMA6BBgAAGAdAgwAALAOAQYAAFiHAAMAAKxDgAEAANYhwAAAAOsQYAAAgHUIMAAAwDoEGAAAYB0CDAAAsA4BBgAAWIcAAwAArEOAAQAA1iHAAAAA6xBgAACAdQgwAADAOgQYAABgHQIMAACwDgEGAABYhwADAACsQ4ABAADWIcAAAADrEGAAAIB1CDAAAMA6BBgAAGAdAgwAALAOAQYAAFiHAAMAAKzTpACTm5ura665Rl27dlVsbKy+853vqLS0NKTmxIkTyszMVI8ePdSlSxdlZGSovLw8pKasrEzp6emKjo5WbGysZs6cqZMnT4bUbNq0SSNGjJDL5VL//v2Vl5d3cUcIAADanSYFmM2bNyszM1Pbtm1TQUGBamtrNWbMGB07dsypmTFjhl555RWtWrVKmzdv1sGDB3X77bc72+vq6pSenq6amhpt3bpVL730kvLy8jR37lynZv/+/UpPT9dNN92kkpISTZ8+Xffee6/Wr1/fDIcMAABsF2aMMRe786effqrY2Fht3rxZo0aNUlVVlS677DItW7ZMd9xxhyRp7969GjRokIqKijRy5Ei9+uqruvXWW3Xw4EHFxcVJkpYsWaLs7Gx9+umnioyMVHZ2tvLz87Vr1y7nvcaPH6/KykqtW7fuguYWDAbl8XhUVVUlt9t9sYcItBn9Zue32NgfzUtvsbEBoCku9PP7kq6BqaqqkiR1795dklRcXKza2lqlpaU5NQMHDlSfPn1UVFQkSSoqKlJycrITXiTJ7/crGAxq9+7dTs2pYzTUNIzRmOrqagWDwZAFAAC0TxcdYOrr6zV9+nR94xvf0JAhQyRJgUBAkZGRiomJCamNi4tTIBBwak4NLw3bG7adqyYYDOr48eONzic3N1cej8dZEhISLvbQAABAG3fRASYzM1O7du3S8uXLm3M+Fy0nJ0dVVVXOcuDAgdaeEgAAaCERF7PTtGnTtHbtWm3ZskW9e/d21nu9XtXU1KiysjLkLEx5ebm8Xq9T89Zbb4WM13CX0qk1p9+5VF5eLrfbraioqEbn5HK55HK5LuZwAACAZZp0BsYYo2nTpmn16tXauHGjEhMTQ7anpKSoY8eOKiwsdNaVlpaqrKxMPp9PkuTz+bRz505VVFQ4NQUFBXK73UpKSnJqTh2joaZhDAAA8NXWpDMwmZmZWrZsmf70pz+pa9euzjUrHo9HUVFR8ng8mjJlirKystS9e3e53W49+OCD8vl8GjlypCRpzJgxSkpK0sSJEzV//nwFAgHNmTNHmZmZzhmUqVOn6tlnn9WsWbN0zz33aOPGjVq5cqXy81vuLgwAAGCPJp2BWbx4saqqqnTjjTeqV69ezrJixQqnZsGCBbr11luVkZGhUaNGyev16uWXX3a2h4eHa+3atQoPD5fP59P3vvc9TZo0SY899phTk5iYqPz8fBUUFGjYsGF66qmn9Pzzz8vv9zfDIQMAANtd0nNg2jKeA4P2hufAAPgq+Jc8BwYAAKA1EGAAAIB1CDAAAMA6BBgAAGAdAgwAALAOAQYAAFiHAAMAAKxDgAEAANYhwAAAAOsQYAAAgHUIMAAAwDoEGAAAYB0CDAAAsA4BBgAAWIcAAwAArEOAAQAA1iHAAAAA6xBgAACAdQgwAADAOgQYAABgHQIMAACwDgEGAABYhwADAACsQ4ABAADWIcAAAADrEGAAAIB1CDAAAMA6BBgAAGAdAgwAALAOAQYAAFiHAAMAAKzT5ACzZcsWfetb31J8fLzCwsK0Zs2akO3f//73FRYWFrKMHTs2pObw4cOaMGGC3G63YmJiNGXKFB09ejSkZseOHbrhhhvUqVMnJSQkaP78+U0/OgAA0C41OcAcO3ZMw4YN06JFi85aM3bsWB06dMhZ/vjHP4ZsnzBhgnbv3q2CggKtXbtWW7Zs0f333+9sDwaDGjNmjPr27avi4mI98cQTeuSRR/Sb3/ymqdMFAADtUERTdxg3bpzGjRt3zhqXyyWv19votvfff1/r1q3T22+/rauvvlqS9Mwzz+iWW27Rk08+qfj4eC1dulQ1NTV64YUXFBkZqcGDB6ukpES//OUvQ4IOAAD4amqRa2A2bdqk2NhYDRgwQA888IA+++wzZ1tRUZFiYmKc8CJJaWlp6tChg7Zv3+7UjBo1SpGRkU6N3+9XaWmpPv/880bfs7q6WsFgMGQBAADtU7MHmLFjx+r3v/+9CgsL9Ytf/EKbN2/WuHHjVFdXJ0kKBAKKjY0N2SciIkLdu3dXIBBwauLi4kJqGl431JwuNzdXHo/HWRISEpr70AAAQBvR5K+Qzmf8+PHOv5OTkzV06FBdeeWV2rRpk0aPHt3cb+fIyclRVlaW8zoYDBJiAABop1r8NuorrrhCPXv21IcffihJ8nq9qqioCKk5efKkDh8+7Fw34/V6VV5eHlLT8Pps19a4XC653e6QBQAAtE8tHmA++eQTffbZZ+rVq5ckyefzqbKyUsXFxU7Nxo0bVV9fr9TUVKdmy5Ytqq2tdWoKCgo0YMAAdevWraWnDAAA2rgmB5ijR4+qpKREJSUlkqT9+/erpKREZWVlOnr0qGbOnKlt27bpo48+UmFhoW677Tb1799ffr9fkjRo0CCNHTtW9913n9566y29+eabmjZtmsaPH6/4+HhJ0t13363IyEhNmTJFu3fv1ooVK7Rw4cKQr4gAAMBXV5MDzDvvvKOrrrpKV111lSQpKytLV111lebOnavw8HDt2LFD3/72t/X1r39dU6ZMUUpKil5//XW5XC5njKVLl2rgwIEaPXq0brnlFl1//fUhz3jxeDx67bXXtH//fqWkpOihhx7S3LlzuYUaAABIksKMMaa1J9ESgsGgPB6PqqqquB4G7UK/2fktNvZH89JbbGwAaIoL/fzmt5AAAIB1CDAAAMA6BBgAAGAdAgwAALAOAQYAAFiHAAMAAKxDgAEAANYhwAAAAOsQYAAAgHUIMAAAwDoEGAAAYB0CDAAAsA4BBgAAWIcAAwAArEOAAQAA1olo7QkA7U2/2fmtPQUAaPc4AwMAAKxDgAEAANYhwAAAAOsQYAAAgHUIMAAAwDoEGAAAYB0CDAAAsA4BBgAAWIcAAwAArEOAAQAA1iHAAAAA6xBgAACAdQgwAADAOgQYAABgHQIMAACwTpMDzJYtW/Stb31L8fHxCgsL05o1a0K2G2M0d+5c9erVS1FRUUpLS9MHH3wQUnP48GFNmDBBbrdbMTExmjJlio4ePRpSs2PHDt1www3q1KmTEhISNH/+/KYfHQAAaJeaHGCOHTumYcOGadGiRY1unz9/vn71q19pyZIl2r59uzp37iy/368TJ044NRMmTNDu3btVUFCgtWvXasuWLbr//vud7cFgUGPGjFHfvn1VXFysJ554Qo888oh+85vfXMQhAgCA9ibMGGMueuewMK1evVrf+c53JH159iU+Pl4PPfSQfvzjH0uSqqqqFBcXp7y8PI0fP17vv/++kpKS9Pbbb+vqq6+WJK1bt0633HKLPvnkE8XHx2vx4sX6yU9+okAgoMjISEnS7NmztWbNGu3du/eC5hYMBuXxeFRVVSW3232xhwg0Wb/Z+a09hSb7aF56a08BACRd+Od3s14Ds3//fgUCAaWlpTnrPB6PUlNTVVRUJEkqKipSTEyME14kKS0tTR06dND27dudmlGjRjnhRZL8fr9KS0v1+eefN+eUAQCAhSKac7BAICBJiouLC1kfFxfnbAsEAoqNjQ2dRESEunfvHlKTmJh4xhgN27p163bGe1dXV6u6utp5HQwGL/FoAABAW9Vu7kLKzc2Vx+NxloSEhNaeEgAAaCHNGmC8Xq8kqby8PGR9eXm5s83r9aqioiJk+8mTJ3X48OGQmsbGOPU9TpeTk6OqqipnOXDgwKUfEAAAaJOaNcAkJibK6/WqsLDQWRcMBrV9+3b5fD5Jks/nU2VlpYqLi52ajRs3qr6+XqmpqU7Nli1bVFtb69QUFBRowIABjX59JEkul0tutztkAQAA7VOTA8zRo0dVUlKikpISSV9euFtSUqKysjKFhYVp+vTp+q//+i/9+c9/1s6dOzVp0iTFx8c7dyoNGjRIY8eO1X333ae33npLb775pqZNm6bx48crPj5eknT33XcrMjJSU6ZM0e7du7VixQotXLhQWVlZzXbgAADAXk2+iPedd97RTTfd5LxuCBWTJ09WXl6eZs2apWPHjun+++9XZWWlrr/+eq1bt06dOnVy9lm6dKmmTZum0aNHq0OHDsrIyNCvfvUrZ7vH49Frr72mzMxMpaSkqGfPnpo7d27Is2IAAMBX1yU9B6Yt4zkwaC08BwYALl6rPAcGAADgX4EAAwAArEOAAQAA1iHAAAAA6xBgAACAdQgwAADAOgQYAABgHQIMAACwDgEGAABYhwADAACsQ4ABAADWIcAAAADrEGAAAIB1CDAAAMA6BBgAAGAdAgwAALAOAQYAAFiHAAMAAKxDgAEAANYhwAAAAOsQYAAAgHUIMAAAwDoEGAAAYB0CDAAAsA4BBgAAWIcAAwAArEOAAQAA1iHAAAAA6xBgAACAdQgwAADAOgQYAABgHQIMAACwTrMHmEceeURhYWEhy8CBA53tJ06cUGZmpnr06KEuXbooIyND5eXlIWOUlZUpPT1d0dHRio2N1cyZM3Xy5MnmnioAALBUREsMOnjwYG3YsOGfbxLxz7eZMWOG8vPztWrVKnk8Hk2bNk2333673nzzTUlSXV2d0tPT5fV6tXXrVh06dEiTJk1Sx44d9fOf/7wlpgsAACzTIgEmIiJCXq/3jPVVVVX63e9+p2XLlunmm2+WJL344osaNGiQtm3bppEjR+q1117Tnj17tGHDBsXFxWn48OF6/PHHlZ2drUceeUSRkZEtMWUAAGCRFrkG5oMPPlB8fLyuuOIKTZgwQWVlZZKk4uJi1dbWKi0tzakdOHCg+vTpo6KiIklSUVGRkpOTFRcX59T4/X4Fg0Ht3r37rO9ZXV2tYDAYsgAAgPap2QNMamqq8vLytG7dOi1evFj79+/XDTfcoCNHjigQCCgyMlIxMTEh+8TFxSkQCEiSAoFASHhp2N6w7Wxyc3Pl8XicJSEhoXkPDAAAtBnN/hXSuHHjnH8PHTpUqamp6tu3r1auXKmoqKjmfjtHTk6OsrKynNfBYJAQAwBAO9Xit1HHxMTo61//uj788EN5vV7V1NSosrIypKa8vNy5Zsbr9Z5xV1LD68auq2ngcrnkdrtDFgAA0D61eIA5evSo9u3bp169eiklJUUdO3ZUYWGhs720tFRlZWXy+XySJJ/Pp507d6qiosKpKSgokNvtVlJSUktPFwAAWKDZv0L68Y9/rG9961vq27evDh48qIcffljh4eG666675PF4NGXKFGVlZal79+5yu9168MEH5fP5NHLkSEnSmDFjlJSUpIkTJ2r+/PkKBAKaM2eOMjMz5XK5mnu6AADAQs0eYD755BPddddd+uyzz3TZZZfp+uuv17Zt23TZZZdJkhYsWKAOHTooIyND1dXV8vv9eu6555z9w8PDtXbtWj3wwAPy+Xzq3LmzJk+erMcee6y5pwoAACwVZowxrT2JlhAMBuXxeFRVVcX1MPiX6jc7v7Wn0GQfzUtv7SkAgKQL//zmt5AAAIB1CDAAAMA6BBgAAGAdAgwAALAOAQYAAFiHAAMAAKxDgAEAANYhwAAAAOsQYAAAgHUIMAAAwDoEGAAAYB0CDAAAsA4BBgAAWIcAAwAArEOAAQAA1iHAAAAA6xBgAACAdQgwAADAOgQYAABgHQIMAACwDgEGAABYhwADAACsQ4ABAADWIcAAAADrRLT2BAC0vn6z81tk3I/mpbfIuADAGRgAAGAdzsDgK6mlzjgAAP41CDAAWkxLBkW+ngK+2vgKCQAAWIczMACAVsHF47gUBBgA+Bfh2iug+bTpALNo0SI98cQTCgQCGjZsmJ555hlde+21rT0tAG0A/+8dZ2NjUOTvrunabIBZsWKFsrKytGTJEqWmpurpp5+W3+9XaWmpYmNjW3t6+Bex8X+IYDf+5gA7hBljTGtPojGpqam65ppr9Oyzz0qS6uvrlZCQoAcffFCzZ88+7/7BYFAej0dVVVVyu90tPd2vNP4HHwAuDWdg/ulCP7/b5BmYmpoaFRcXKycnx1nXoUMHpaWlqaioqNF9qqurVV1d7byuqqqS9GUjbDLk4fWtPQUAwL9YnxmrWnsKTbbrUX+LjNvwuX2+8yttMsD83//9n+rq6hQXFxeyPi4uTnv37m10n9zcXD366KNnrE9ISGiROQIA8FXmebplxz9y5Ig8Hs9Zt7fJAHMxcnJylJWV5byur6/X4cOH1aNHD4WFhbXizL5MkwkJCTpw4ABfZzUj+tr86Gnzo6ctg742v7bSU2OMjhw5ovj4+HPWtckA07NnT4WHh6u8vDxkfXl5ubxeb6P7uFwuuVyukHUxMTEtNcWL4na7+Q+tBdDX5kdPmx89bRn0tfm1hZ6e68xLgzb5JN7IyEilpKSosLDQWVdfX6/CwkL5fL5WnBkAAGgL2uQZGEnKysrS5MmTdfXVV+vaa6/V008/rWPHjukHP/hBa08NAAC0sjYbYO688059+umnmjt3rgKBgIYPH65169adcWGvDVwulx5++OEzvuLCpaGvzY+eNj962jLoa/Ozradt9jkwAAAAZ9Mmr4EBAAA4FwIMAACwDgEGAABYhwADAACsQ4CR1K9fP4WFhZ2xZGZmhtQZYzRu3DiFhYVpzZo1IdvKysqUnp6u6OhoxcbGaubMmTp58mRIzaZNmzRixAi5XC71799feXl5Z8xl0aJF6tevnzp16qTU1FS99dZbIdtPnDihzMxM9ejRQ126dFFGRsYZD/xrCy6kp0VFRbr55pvVuXNnud1ujRo1SsePH3e2Hz58WBMmTJDb7VZMTIymTJmio0ePhrzPjh07dMMNN6hTp05KSEjQ/Pnzz5jLqlWrNHDgQHXq1EnJycn6y1/+ErLdGKO5c+eqV69eioqKUlpamj744INm7kjzOF9fA4GAJk6cKK/Xq86dO2vEiBH6n//5n5Ax6Guouro6/fSnP1ViYqKioqJ05ZVX6vHHHw/5HZYLORb6+k/n62ltba2ys7OVnJyszp07Kz4+XpMmTdLBgwdDxqGnoS7kb/VUU6dOVVhYmJ5++umQ9e2mrwamoqLCHDp0yFkKCgqMJPPXv/41pO6Xv/ylGTdunJFkVq9e7aw/efKkGTJkiElLSzPvvvuu+ctf/mJ69uxpcnJynJp//OMfJjo62mRlZZk9e/aYZ555xoSHh5t169Y5NcuXLzeRkZHmhRdeMLt37zb33XefiYmJMeXl5U7N1KlTTUJCgiksLDTvvPOOGTlypLnuuutarDcX63w93bp1q3G73SY3N9fs2rXL7N2716xYscKcOHHCGWPs2LFm2LBhZtu2beb11183/fv3N3fddZezvaqqysTFxZkJEyaYXbt2mT/+8Y8mKirK/PrXv3Zq3nzzTRMeHm7mz59v9uzZY+bMmWM6duxodu7c6dTMmzfPeDwes2bNGvPee++Zb3/72yYxMdEcP3685RvVROfr6ze/+U1zzTXXmO3bt5t9+/aZxx9/3HTo0MH87W9/c8agr6F+9rOfmR49epi1a9ea/fv3m1WrVpkuXbqYhQsXOjUXciz09Z/O19PKykqTlpZmVqxYYfbu3WuKiorMtddea1JSUkLGoaehLuRvtcHLL79shg0bZuLj482CBQtCtrWXvhJgGvGjH/3IXHnllaa+vt5Z9+6775rLL7/cHDp06IwA85e//MV06NDBBAIBZ93ixYuN2+021dXVxhhjZs2aZQYPHhzyPnfeeafx+/3O62uvvdZkZmY6r+vq6kx8fLzJzc01xnz5H33Hjh3NqlWrnJr333/fSDJFRUXNc/At5PSepqammjlz5py1fs+ePUaSefvtt511r776qgkLCzP/+7//a4wx5rnnnjPdunVzemyMMdnZ2WbAgAHO6+9+97smPT09ZOzU1FTzwx/+0BhjTH19vfF6veaJJ55wtldWVhqXy2X++Mc/XsIR/2uc3tfOnTub3//+9yE13bt3N7/97W+NMfS1Menp6eaee+4JWXf77bebCRMmGGMu7Fjoa6jz9bQxb731lpFkPv74Y2MMPW3Mhfb1k08+MZdffrnZtWuX6du3b0iAaU995Suk09TU1OgPf/iD7rnnHudHIL/44gvdfffdWrRoUaO/xVRUVKTk5OSQh+z5/X4Fg0Ht3r3bqUlLSwvZz+/3q6ioyHnf4uLikJoOHTooLS3NqSkuLlZtbW1IzcCBA9WnTx+npi06vacVFRXavn27YmNjdd111ykuLk7/9m//pjfeeMPZp6ioSDExMbr66quddWlpaerQoYO2b9/u1IwaNUqRkZFOjd/vV2lpqT7//HOn5lx9379/vwKBQEiNx+NRampqm+6p1Pjf6nXXXacVK1bo8OHDqq+v1/Lly3XixAndeOONkuhrY6677joVFhbq73//uyTpvffe0xtvvKFx48ZJurBjoa+hztfTxlRVVSksLMz5DTt6eqYL6Wt9fb0mTpyomTNnavDgwWeM0Z762mafxNta1qxZo8rKSn3/+9931s2YMUPXXXedbrvttkb3CQQCZzwhuOF1IBA4Z00wGNTx48f1+eefq66urtGavXv3OmNERkae8SOVcXFxzvu0Raf39B//+Ick6ZFHHtGTTz6p4cOH6/e//71Gjx6tXbt26Wtf+5oCgYBiY2NDxomIiFD37t1DepqYmBhSc2rfu3Xrdta+nzrGqfs1VtNWNfa3unLlSt15553q0aOHIiIiFB0drdWrV6t///6SRF8bMXv2bAWDQQ0cOFDh4eGqq6vTz372M02YMEHShR0LfQ11vp6e7sSJE8rOztZdd93l/IggPT3ThfT1F7/4hSIiIvSf//mfjY7RnvpKgDnN7373O40bN875Ge8///nP2rhxo959991Wnpm9Tu9pfX29JOmHP/yh89tWV111lQoLC/XCCy8oNze31eZqk9P7Kkk//elPVVlZqQ0bNqhnz55as2aNvvvd7+r1119XcnJyK8627Vq5cqWWLl2qZcuWafDgwSopKdH06dMVHx+vyZMnt/b0rNSUntbW1uq73/2ujDFavHhxK83YDufra3FxsRYuXKi//e1vzlnZ9oyvkE7x8ccfa8OGDbr33nuddRs3btS+ffsUExOjiIgIRUR8mfkyMjKc0/Jer/eMO4EaXjd85XS2GrfbraioKPXs2VPh4eGN1pw6Rk1NjSorK89a09Y01tNevXpJkpKSkkJqBw0apLKyMklfHmtFRUXI9pMnT+rw4cPn7WnDtnPVnLr91P0aq2mLGuvrvn379Oyzz+qFF17Q6NGjNWzYMD388MO6+uqrtWjRIkn0tTEzZ87U7NmzNX78eCUnJ2vixImaMWOGE6Qv5Fjoa6jz9bRBQ3j5+OOPVVBQ4Jx9kehpY87X19dff10VFRXq06eP83n18ccf66GHHlK/fv0kta++EmBO8eKLLyo2Nlbp6enOutmzZ2vHjh0qKSlxFklasGCBXnzxRUmSz+fTzp07Q/4oGv5jbPiQ9vl8KiwsDHm/goIC+Xw+SVJkZKRSUlJCaurr61VYWOjUpKSkqGPHjiE1paWlKisrc2ramsZ62q9fP8XHx6u0tDSk9u9//7v69u0r6ct+VVZWqri42Nm+ceNG1dfXKzU11anZsmWLamtrnZqCggINGDBA3bp1c2rO1ffExER5vd6QmmAwqO3bt7fZnkqN9/WLL76Q9OW1U6cKDw93znrR1zN98cUX5+zZhRwLfQ11vp5K/wwvH3zwgTZs2KAePXqE1NPTM52vrxMnTjzj8yo+Pl4zZ87U+vXrJbWzvjbLpcDtQF1dnenTp4/Jzs4+b63Ochv1mDFjTElJiVm3bp257LLLGr2NeubMmeb99983ixYtavQ2apfLZfLy8syePXvM/fffb2JiYkLubpo6darp06eP2bhxo3nnnXeMz+czPp+veZrQzM7V0wULFhi3221WrVplPvjgAzNnzhzTqVMn8+GHHzo1Y8eONVdddZXZvn27eeONN8zXvva1kFv9KisrTVxcnJk4caLZtWuXWb58uYmOjj7jVr+IiAjz5JNPmvfff988/PDDjd7qFxMTY/70pz+ZHTt2mNtuu61N3kLZ4Gx9rampMf379zc33HCD2b59u/nwww/Nk08+acLCwkx+fr5TR19DTZ482Vx++eXOrakvv/yy6dmzp5k1a5ZTcyHHQl//6Xw9rampMd/+9rdN7969TUlJScijAU6984WehrqQv9XTnX4XkjHtp68EmP9v/fr1RpIpLS09b+3pAcYYYz766CMzbtw4ExUVZXr27GkeeughU1tbG1Lz17/+1QwfPtxERkaaK664wrz44otnjP3MM8+YPn36mMjISHPttdeabdu2hWw/fvy4+Y//+A/TrVs3Ex0dbf793//dHDp0qMnH+69wvp7m5uaa3r17m+joaOPz+czrr78esv2zzz4zd911l+nSpYtxu93mBz/4gTly5EhIzXvvvWeuv/5643K5zOWXX27mzZt3xvusXLnSfP3rXzeRkZFm8ODBIR/mxnx5u99Pf/pTExcXZ1wulxk9evQF/R20lnP19e9//7u5/fbbTWxsrImOjjZDhw4947Zq+hoqGAyaH/3oR6ZPnz6mU6dO5oorrjA/+clPQj5IL+RY6Os/na+n+/fvN5IaXU59/hY9DXUhf6unayzAtJe+hhlzlkf4AQAAtFFcAwMAAKxDgAEAANYhwAAAAOsQYAAAgHUIMAAAwDoEGAAAYB0CDAAAsA4BBgAAWIcAAwAArEOAAQAA1iHAAAAA6xBgAACAdf4fI4++61oPOycAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#savedHDunitList = [HDunitList[t].copy() for t in range(nHDs) ]  #safekeeping\n",
    "HDunitList = [savedHDunitList[t].copy() for t in range(nHDs) ]   #restart\n",
    "HDvPop = [0 for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "plt.hist([HDvPop[t] for t in popHDlist],bins=20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "551454fb-d57c-466f-8b31-39ccb2a728de",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here are the HD centers for 178 cantFill HDs with border or big enclaves\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"here are the HD centers for\",len(cantFill),\"cantFill HDs with border or big enclaves\")\n",
    "for u in borderUnits:\n",
    "    plotPoly(unitGeom[u])\n",
    "for t in cantFill:\n",
    "    plotPoly(hdCP[t].buffer(0.02))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "5269a224-4a97-417c-99af-6a98df0087ae",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on avg unit-to-HDcp dist for HD 0\n",
      "working on avg unit-to-HDcp dist for HD 800\n",
      "working on avg unit-to-HDcp dist for HD 1601\n",
      "working on avg unit-to-HDcp dist for HD 2403\n",
      "working on avg unit-to-HDcp dist for HD 3203\n",
      "working on avg unit-to-HDcp dist for HD 4003\n",
      "working on avg unit-to-HDcp dist for HD 4803\n",
      "working on avg unit-to-HDcp dist for HD 5604\n",
      "all unit-toHDcp distances computed\n"
     ]
    }
   ],
   "source": [
    "barredJettisonSet = set([6197, 6198] )  #lock in the clusters  #update this for each state - see CCB report 3 blocks up\n",
    "avgDist = [0. for t in range(nHDs)]  #about 6sec per 1000 HDs\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%800 == 0:\n",
    "        print(\"working on avg unit-to-HDcp dist for HD\",t)\n",
    "    avgDist[t] =  np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]\n",
    "print(\"all unit-toHDcp distances computed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "6e2e44bd-a084-42f6-b533-5dc6d21912a9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this code will solve large enclaves so HD and complement are contiguous for 178 HDs\n",
      "working on HD 82 cantFill 0 of 178 .Time is now 0\n",
      "working on HD 2035 cantFill 20 of 178 .Time is now 12\n",
      "working on HD 2114 cantFill 40 of 178 .Time is now 25\n",
      "working on HD 2273 cantFill 60 of 178 .Time is now 37\n",
      "working on HD 4936 cantFill 80 of 178 .Time is now 47\n",
      "working on HD 5953 cantFill 100 of 178 .Time is now 50\n",
      "working on HD 6028 cantFill 120 of 178 .Time is now 50\n",
      "working on HD 6185 cantFill 140 of 178 .Time is now 52\n",
      "working on HD 2141 cantFill 160 of 178 .Time is now 60\n",
      "after the MustFree code run, we have the following for cluster usage\n",
      "current avg use and its sd are 1.00419 0.10971\n",
      "CCB cluster 0 = unit 6197 with pop 95263.0 now has use of 1.0002973411329803\n",
      "CCB cluster 1 = unit 6198 with pop 64837.0 now has use of 0.9982342544305851\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#THIS IS THE MUSTFREE CODE - for high-pop HDs with map-border enclaves, can't fill; \n",
    "#  must jettison some inHD map-boundary units to connect the enclave to the larger complement\n",
    "#For each HD to be triaged, define the list(s) of contiguous enclave units that are on the map boundary, \n",
    "#  and the in-HD map-boundary segments.  ID which in-HD MBS's adjoin one vs. two enclaves.\n",
    "#     Fill all internal enclaves, and all boundary enclaves < 0.05 aDP.\n",
    "#   Then each loop, look for boundary enclaves that can be filled without overpopping.\n",
    "#     If none, pick the 1/2 has-1-boundary-enclave-neighbor that is least painful to jettison to free an enclave.\n",
    "#       (Jettison score based on pop-to-Free and distance from HDcP)\n",
    "#         Update HDpop, HDlist, and enclave & HD-boundary associations, then re-loop\n",
    "# Later, we will swell-fill to square up pop (w/ checkEnclave) biasing toward close-to-hdCP, underused\n",
    "borderSet = set(borderUnits)\n",
    "debug, debugPlot = False, False\n",
    "startTime = time.time()  #takes about 1.5sec per HD triage\n",
    "clusterJettisonBoost = 3.  #this discourages jettisoning of underused clusters\n",
    "print(\"this code will solve large enclaves so HD and complement are contiguous for\",len(cantFill),\"HDs\")\n",
    "nEnclavesPerHD = [0 for t in range(nHDs)]\n",
    "HDenclaveLists = [list() for t in range(nHDs)]\n",
    "for iii,t in enumerate(cantFill):\n",
    "    if iii %20 == 0:\n",
    "        print(\"working on HD\",t,\"cantFill\",iii,\"of\",len(cantFill),\".Time is now\",int(time.time() - startTime) )\n",
    "    shedUs = list()    \n",
    "    enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "    nEnclavesPerHD[t] = len(enclaveLists)\n",
    "    HDenclaveLists[t] = enclaveLists.copy()\n",
    "    if debug:\n",
    "        print(\"pre-adjust HDpop for HD\",t,\"is\",HDvPop[t],\"I found\",len(enclaveLists),\"TOTAL enclaves\")\n",
    "    internalEnclaves, edgeEnclaves, combinedEnclBorderList = list(), list(), list()\n",
    "    for jjj, eL in enumerate(enclaveLists.copy() ):\n",
    "        enclaveBorderList = list ( set(eL).intersection(borderSet) )\n",
    "        if debug:\n",
    "            print(\"In enclave\",jjj,\"I found\",len(enclaveBorderList),\"units that were enclaved and are in the map borderSet\")\n",
    "        combinedEnclBorderList += enclaveBorderList\n",
    "        ePop = np.sum( [unitPop[u] for u in eL] )\n",
    "        if len(enclaveBorderList) == 0 or ePop < 0.05 * aDP:  #internal or small enclave.  Fill it\n",
    "            if ePop > 0:  #in a prev treatment, could be an empty (surrounded) unit that we don't care about\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += ePop\n",
    "            internalEnclaves.append(eL)\n",
    "        else:\n",
    "            edgeEnclaves.append(eL)\n",
    "    if debug:\n",
    "        print(\"Of these\",len(internalEnclaves),\"were internal or small, so I filled them, leaving\",\n",
    "              len(edgeEnclaves),\"non-small border = edge enclaves\" )\n",
    "    if debugPlot:\n",
    "        print(\"Here is the original HD, internal enclaves ('x') and non-small border enclaves by enclave no\")\n",
    "        plotPoly(hdCP[t].buffer(0.3))\n",
    "        for u in HDunitList[t]:\n",
    "            if unitPop[u] > 0:\n",
    "                plotPoly(unitGeom[u],0.2)\n",
    "        for L in internalEnclaves:\n",
    "            for u in L:\n",
    "                if unitPop[u] > 0:\n",
    "                    plotPoly(unitGeom[u],1.5)\n",
    "                    plotCenter(\"x\",unitCP[u],8)\n",
    "        for L in edgeEnclaves: #############\n",
    "            for u in L:\n",
    "                if unitPop[u] > 0:\n",
    "                    plotPoly(unitGeom[u])\n",
    "                    #plotCenter(\"e\",unitCP[u],8)\n",
    "        #plotPoly(MAP,0.4)\n",
    "        #plt.show()\n",
    "    enclaveLists, combinedEnclBorderSet = list(), set(combinedEnclBorderList)\n",
    "    if len(edgeEnclaves) > 0:\n",
    "        # Now, we order by chain connectivity of HD and enclave sublists to be H0-E0-H1-E1 ... En-Hn+1\n",
    "        nonHDborderSet = borderSet.difference(  set(HDunitList[t]) )\n",
    "        nonHDlongBorderSet = nonHDborderSet.difference(combinedEnclBorderSet) #long=non HD boundary excluding enclaves\n",
    "        remainingEnclBorderSet = combinedEnclBorderSet.copy()\n",
    "        remainingHDborderSet =   borderSet.intersection(set(HDunitList[t]) )\n",
    "        #Now find the \"HDender\" unit which borders the non-enclave nonHD boundary, then find opp end of this HD bdry piece\n",
    "        HDender = list(set(getAdjoiners(nonHDlongBorderSet,unitNbrs)).intersection(remainingHDborderSet) )[0]\n",
    "        firstHDborderSet = getContigFromStarter(HDender,remainingHDborderSet,unitNbrs)\n",
    "        HDstarter = list(set(getAdjoiners(remainingEnclBorderSet,unitNbrs)).intersection(firstHDborderSet))[0]\n",
    "        HDborderSublists = [ list(firstHDborderSet) ]\n",
    "        unused = [1 for eL in edgeEnclaves]\n",
    "        eLadjoiners = [getAdjoiners(eL,unitNbrs) for eL in edgeEnclaves ]\n",
    "        for j in range(len(edgeEnclaves)): #find the enclave with the most HDstarter neighbors (at least 1)\n",
    "            found = False\n",
    "            for i,eL in enumerate(edgeEnclaves):\n",
    "                if unused[i] == 1:\n",
    "                    HDadjSet = set(HDborderSublists[j]).intersection(set(eLadjoiners[i]))\n",
    "                    if len(HDadjSet) > 0:\n",
    "                        unused[i] = 0\n",
    "                        eNo = i\n",
    "                        found = True\n",
    "                        remainingEnclBorderSet = remainingEnclBorderSet.difference(set(edgeEnclaves[eNo]) )\n",
    "                        enclaveLists.append(edgeEnclaves[eNo])\n",
    "                        remainingHDborderSet = remainingHDborderSet.difference(set(HDborderSublists[j]) )\n",
    "                        HDstarter = list(set(eLadjoiners[i]).intersection(remainingHDborderSet))[0]       \n",
    "                        HDborderSublists.append(getContigFromStarter(HDstarter,remainingHDborderSet,unitNbrs) )\n",
    "                        break\n",
    "                if found:\n",
    "                    break\n",
    "\n",
    "        enclavePops = [np.sum([unitPop[u] for u in L]) for L in enclaveLists]\n",
    "        #print(\"prior to adjustments, border enclavePops are\",enclavePops)         \n",
    "\n",
    "        nHDBS, nEnclaves = len(HDborderSublists), len(enclaveLists)\n",
    "        popToFree, freeingCounties, freeingUnits = [0. for n in range(nHDBS)], [list() for n in range(nHDBS) \n",
    "                                                                               ],[list() for n in range(nHDBS)]\n",
    "        for j,L in enumerate(HDborderSublists):\n",
    "            for u in L:\n",
    "                if int(allUnits[u]) == allUnits[u]:  #this border unit is a vtd\n",
    "                    c = countyNo[parentVTDno[allUnits[u]]]   #countyNo[allUnits[u]]\n",
    "                    if c not in freeingCounties[j]:\n",
    "                        if countyPop[c] < 0.1 * aDP:  #plan to add all in-county pop\n",
    "                            freeingCounties[j].append(c)\n",
    "                        else:\n",
    "                            popToFree[j] += unitPop[u]\n",
    "                            freeingUnits[j].append(u)\n",
    "                else: #border unit is a full county or cluster, or in a dense county.  Add the whole unit pop\n",
    "                    popToFree[j] += unitPop[u]\n",
    "                    freeingUnits[j].append(u)\n",
    "            for c in freeingCounties[j]:  #include ALL in-HD pop from each non-unit border county, not just its border units\n",
    "                #plotPoly(countyGeom[c],0.1)\n",
    "                for u in countyUnitList[c]:\n",
    "                    if u in HDunitList[t]:\n",
    "                        popToFree[j] += unitPop[u]\n",
    "                        freeingUnits[j].append(u)\n",
    "        freeingCP = [ getHDcp(  unitCP, unitPop, L) for L in freeingUnits ]\n",
    "        freeingScore = [ pTF/aDP - 0.5*freeingCP[j].distance(hdCP[t]) / avgDist[t] for j,pTF in enumerate(popToFree) ]\n",
    "        for j, fU in enumerate(freeingUnits):  #in above 0.5 is a fudgy\n",
    "            if len(barredJettisonSet.intersection(set(fU)) ) > 0: #has a cluster we want to hold onto\n",
    "                freeingScore[j] += clusterJettisonBoost #  ..so increase its score (make it harder to drop)\n",
    "        if debugPlot:\n",
    "            print(\"plotting the freeing units with negative numbers for each freeing group\")\n",
    "            for j,L in enumerate(freeingUnits):\n",
    "                for u in L:\n",
    "                    if unitPop[u] > 0:\n",
    "                        #plotPoly(unitGeom[u],0.5)\n",
    "                        plotCenter(\"-\"+str(j),unitGeom[u],6)\n",
    "                        pass\n",
    "            print(\"plotting the enclaveLists, with + numbers for each enclave\")\n",
    "            for j,L in enumerate(enclaveLists):\n",
    "                for u in L:\n",
    "                    if unitPop[u] > 0:\n",
    "                        plotPoly(unitGeom[u])\n",
    "                        plotCenter(j,unitCP[u],8)\n",
    "                        pass\n",
    "    \n",
    "    while len(enclaveLists) > 0:\n",
    "        if HDvPop[t] + np.min(enclavePops) < 1.05*aDP or np.min(enclavePops) < 0.05 * aDP:  #fill the smallest enclave\n",
    "            eNo = enclavePops.index(np.min(enclavePops))\n",
    "            HDunitList[t] += enclaveLists[eNo]\n",
    "            HDvPop[t] += enclavePops[eNo]\n",
    "            #print(t,\"=t. Absorbing enclave\",eNo,\"with pop\",enclavePops[eNo],\"HD total pop now\",int(HDfreePop[t]) )\n",
    "            enclaveBUs = list(set(enclaveLists[eNo]).intersection(set(borderUnits)) )\n",
    "            enclaveBpop = np.sum([unitPop[u] for u in enclaveBUs])\n",
    "            sNo, dropped_sNo = eNo, eNo+1\n",
    "            freeingScore[sNo] += freeingScore[sNo+1]+enclaveBpop/aDP\n",
    "            freeingUnits[sNo] += freeingUnits[sNo+1]+enclaveBUs\n",
    "            popToFree[sNo]    +=    popToFree[sNo+1]+enclaveBpop\n",
    "        else: #jettison one of the two end HD border lists; pick the less painful path to freedom\n",
    "            distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "            starterU = HDunitList[t][distList.index(np.min(distList))]\n",
    "            eNo, dropped_sNo = 0,0\n",
    "            if starterU not in freeingUnits[-1]:  #we can't drop the home unit, even to save an underused corner\n",
    "                if freeingScore[-1] < freeingScore[0] or starterU in freeingUnits[0]:\n",
    "                    eNo, dropped_sNo = len(enclaveLists)-1,len(enclaveLists)\n",
    "            barredIncluded0 = barredJettisonSet.intersection(set(freeingUnits[0]))\n",
    "            barredIncluded_1 = barredJettisonSet.intersection(set(freeingUnits[-1]))\n",
    "            #if len(barredIncluded0.union(barredIncluded_1)) > 0:\n",
    "            #    print(\"We are considering dropping an end unit to free from t\",t,\". Chosen, beg, end, scores are\")\n",
    "            #    print(dropped_sNo,barredIncluded0, barredIncluded_1, freeingScore[0], freeingScore[-1])\n",
    "            HDunitList[t] = list( set(HDunitList[t]).difference(set(freeingUnits[dropped_sNo]) ) )\n",
    "            HDvPop[t] -= popToFree[dropped_sNo]\n",
    "            #print(t,\"= t. Jettisoning HDborder\",dropped_sNo,\"with popToFree\",popToFree[dropped_sNo] )\n",
    "        del enclaveLists[eNo]\n",
    "        del enclavePops[eNo]\n",
    "        if debug:\n",
    "            print(t,\"= t. Now we have\",len(enclaveLists),\"left trapped.  Picked eNo, freeScores were\", eNo,freeingScore)\n",
    "        del freeingScore[dropped_sNo]\n",
    "        del freeingUnits[dropped_sNo]\n",
    "        del popToFree   [dropped_sNo] \n",
    "\n",
    "    #plotPoly(MAP,0.4)\n",
    "    if debugPlot:\n",
    "        plt.show()    \n",
    "        \n",
    "unitUse = [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t]*nDistricts\n",
    "print(\"after the MustFree code run, we have the following for cluster usage\")\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "for u, unitNo in enumerate(allUnits):\n",
    "    if unitNo % 1 == 0.25:\n",
    "        print(\"CCB cluster\",int(unitNo),\"= unit\",u,\"with pop\",unitPop[u],\"now has use of\",unitUse[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "ca9ce3cb-c150-4f39-ae55-f781d39d7f57",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "postMustFreeUnitList = [HDunitList[t].copy() for t in range(nHDs)] #safekeeping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "c32dd108-073b-48aa-99ce-fea50c8d023c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist([HDvPop[t] for t in popHDlist] )\n",
    "plt.axvline(aDP,ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "f58fe2d0-3c62-412f-8984-ff5d67ea9b10",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "After above work, re-classification of contiguity problems?\n",
      "working on HD 0\n",
      "working on HD 500\n",
      "working on HD 1000\n",
      "working on HD 1500\n",
      "working on HD 2000\n",
      "working on HD 2500\n",
      "working on HD 3000\n",
      "working on HD 3500\n",
      "working on HD 4000\n",
      "working on HD 4500\n",
      "working on HD 5000\n",
      "working on HD 5500\n",
      "working on HD 6000\n",
      "out of 6356 total HDs, there were 5831 77 1 447 HDs that were clean, discontig only, enclave-only, both problems after triage\n"
     ]
    }
   ],
   "source": [
    "#THIS is the FINDSTILLBROKEN code\n",
    "print(\"After above work, re-classification of contiguity problems?\")\n",
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()\n",
    "for t in popHDlist:\n",
    "    if t%500 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems after triage\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "1ef683a2-4429-4a91-b1ea-a9b0950dea22",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on current HD diam for HD number 0\n",
      "working on current HD diam for HD number 800\n",
      "working on current HD diam for HD number 1601\n",
      "working on current HD diam for HD number 2403\n",
      "working on current HD diam for HD number 3203\n",
      "working on current HD diam for HD number 4003\n",
      "working on current HD diam for HD number 4803\n",
      "working on current HD diam for HD number 5604\n",
      "here is the histogram of HD diameter = sqrt(area)\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "HDdiam = [0. for t in range(nHDs)]\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%800 == 0:\n",
    "        print(\"working on current HD diam for HD number\",t)\n",
    "    HDdiam[t] = (HDpoly[t].intersection(MAP) ).area ** 0.5\n",
    "plt.hist([HDdiam[t] for t in popHDlist])\n",
    "print(\"here is the histogram of HD diameter = sqrt(area)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "45e3c17c-8c16-4bc5-b7fc-25b9250ed11a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here, we will regrow all disco'd HDs off by more than  38704 but less than 193520\n",
      "... from the contiguous block that contains the hdCP (not full regrowth).  We will swell out, avoiding enclaves\n",
      "This is a total of 524 HDs to triage in this block\n",
      "working on swell-filling discontig HD 97 our 1 th HD we think we can swell out of 524\n",
      "working on swell-filling discontig HD 2855 our 41 th HD we think we can swell out of 524\n",
      "working on swell-filling discontig HD 164 our 81 th HD we think we can swell out of 524\n",
      "working on swell-filling discontig HD 678 our 121 th HD we think we can swell out of 524\n",
      "working on swell-filling discontig HD 897 our 161 th HD we think we can swell out of 524\n",
      "working on swell-filling discontig HD 1168 our 201 th HD we think we can swell out of 524\n",
      "working on swell-filling discontig HD 1522 our 241 th HD we think we can swell out of 524\n",
      "working on swell-filling discontig HD 2300 our 281 th HD we think we can swell out of 524\n",
      "working on swell-filling discontig HD 3326 our 321 th HD we think we can swell out of 524\n",
      "working on swell-filling discontig HD 4547 our 361 th HD we think we can swell out of 524\n",
      "working on swell-filling discontig HD 4954 our 401 th HD we think we can swell out of 524\n",
      "working on swell-filling discontig HD 5245 our 441 th HD we think we can swell out of 524\n",
      "working on swell-filling discontig HD 5455 our 481 th HD we think we can swell out of 524\n",
      "working on swell-filling discontig HD 6133 our 521 th HD we think we can swell out of 524\n",
      "we partially regrew 500 HDs, leaving 25 to regrow from scratch\n"
     ]
    }
   ],
   "source": [
    "### THIS IS THE CANSWELL CODE\n",
    "print(\"Here, we will regrow all disco'd HDs off by more than \",int(aDP-minPostFixPop),\"but less than\",int(0.25*aDP) )\n",
    "print(\"... from the contiguous block that contains the hdCP (not full regrowth).  We will swell out, avoiding enclaves\")\n",
    "HDnAddedUnits = [0 for t in range(nHDs)]\n",
    "maxGap = 0.9 * np.median(unitPop)  #set a reasonable gap prior to picking the last block\n",
    "HDdiam = [HDpoly[t].area ** 0.5 for t in range(nHDs) ] #in case not defined before\n",
    "badDiscoList = list()\n",
    "nCanSwell = 0\n",
    "triageList = discontigOnly + bothProblems\n",
    "print(\"This is a total of\",len(triageList),\"HDs to triage in this block\")\n",
    "startTime = time.time()\n",
    " \n",
    "for i,t in enumerate(triageList): #canSwell\n",
    "    if i%40 == 0:\n",
    "        SEC = r3(time.time()-startTime)\n",
    "        print(\"working on swell-filling discontig HD\",t,\"our\",i+1,\"th HD we think we can swell out of\",len(triageList),SEC,\"sec elapsed\" )\n",
    "    distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "    starterU = HDunitList[t][distList.index(np.min(distList))]  #starter = unit with centroid closest to the hd center\n",
    "    contigUs = getContigFromStarter(starterU, HDunitList[t], unitNbrs)\n",
    "    contigPop = np.sum( [ unitPop[u] for u in contigUs ] )\n",
    "    if contigPop < 0.50 * aDP or contigPop > 2.*aDP - minPostFixPop:  #formerly < 0.75 aDP\n",
    "        badDiscoList.append(t)\n",
    "    else: #rebuild from this big piece\n",
    "        nCanSwell +=1\n",
    "        gap = aDP - contigPop\n",
    "        origGap = gap\n",
    "        currList, addedList = contigUs.copy(), list()\n",
    "        adjoiners = getAdjoiners(currList, unitNbrs)\n",
    "        nearHDlist = [uu for uu in adjoiners]  #bias toward underused, close to HD (and its center)\n",
    "        nearHDscore = [ (unitUse[uu] - 1.) + 0.5*(unitCP[uu].distance(\n",
    "            HDpoly[t]) + unitCP[uu].distance(hdCP[t]) ) / HDdiam[t] for uu in adjoiners ] \n",
    "        stillGoing = True\n",
    "\n",
    "        while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "            idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "            while i < len(nearHDscore) and notYetPicked:        \n",
    "                listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "                unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "                canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "                if canAdd:\n",
    "                    notYetPicked = False\n",
    "                else:\n",
    "                    i +=1\n",
    "            if notYetPicked:\n",
    "                stillGoing = False  #can't add any more units without creating an enclave\n",
    "            else: #we selected the best unit to add legally\n",
    "                gap -= unitPop[unitNoToAdd]\n",
    "                addedList.append(unitNoToAdd)  #so add it to our growing HD ...\n",
    "                currList.append( unitNoToAdd)\n",
    "                for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                    if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap:  \n",
    "                        nearHDlist.append(uu)\n",
    "                        nearHDscore.append((unitUse[uu] - 1.) + 0.5*(unitCP[uu].distance(\n",
    "                            HDpoly[t]) + unitCP[uu].distance(hdCP[t]) ) / HDdiam[t] )\n",
    "                del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "                del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "                for i, uu in enumerate(nearHDlist.copy()):\n",
    "                    if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                        del nearHDscore[nearHDlist.index(uu)]\n",
    "                        del nearHDlist[ nearHDlist.index(uu)]\n",
    "        for u in addedList:\n",
    "            unitUse[u] += HDweight[t] * nDistricts\n",
    "        for u in list( set(HDunitList[t]).difference(set(contigUs)) ):\n",
    "            unitUse[u] -= HDweight[t] * nDistricts       \n",
    "        HDunitList[t] = contigUs + addedList\n",
    "        HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "        HDnAddedUnits[t] = len(addedList)\n",
    "    \n",
    "badDiscoList += enclaveOnly\n",
    "print(\"we partially regrew\",nCanSwell,\"HDs, leaving\",len(badDiscoList),\"to regrow from scratch\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "f57325dd-523c-466a-80cb-8e10b739b4ac",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "previous avg use and its sd are 1.00419 0.10971\n",
      "defining and displaying current unit use after above manipulations; compare to original farther above.\n",
      "current avg use and its sd are 1.00319 0.10168\n",
      "CCB cluster 0 = unit 6197 with pop 95263.0 now has use of 0.9955730405251859\n",
      "CCB cluster 1 = unit 6198 with pop 64837.0 now has use of 0.9761707241925401\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"previous avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "print(\"defining and displaying current unit use after above manipulations; compare to original farther above.\")\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "\n",
    "for u, unitNo in enumerate(allUnits):\n",
    "    if unitNo % 1 == 0.25:\n",
    "        print(\"CCB cluster\",int(unitNo),\"= unit\",u,\"with pop\",unitPop[u],\"now has use of\",unitUse[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "0ce918e1-0d30-4930-9fb8-0769d793683c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "quick classification: who has contiguity problems?\n",
      "working on HD 0 time is now 0\n",
      "working on HD 1000 time is now 11\n",
      "working on HD 2002 time is now 22\n",
      "working on HD 3003 time is now 34\n",
      "working on HD 4003 time is now 43\n",
      "working on HD 5003 time is now 52\n",
      "working on HD 6004 time is now 62\n",
      "out of 6356 total HDs, there were 6332.0 contiguous and 6304.0 complement-contiguous HDs\n",
      "17 HDs had both discontiguity problems, while enclave-only = 35 and discontig only= 7\n",
      "here are the histograms of the small piece and enclave list lengths, total no = 24 35\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "And here are the small-HD-piece and small-enclave pops\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#THIS is the FINDSTILLBROKEN code\n",
    "print(\"quick classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%1000 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )\n",
    "\n",
    "print(\"here are the histograms of the small piece and enclave list lengths, total no =\",\n",
    "      len(smallPieceLists),len(enclaveLists) )\n",
    "plt.hist([s for s in smallPieceLengths],label=\"small piece l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "plt.hist([e for e in enclaveLengths],label=\"enclave l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "plt.legend()\n",
    "plt.show()\n",
    "print(\"And here are the small-HD-piece and small-enclave pops\")\n",
    "plt.hist([sum(unitPop[u] for u in s) for s in smallPieceLists],label=\"small piece 1 pop\",histtype='step')\n",
    "plt.hist([sum(unitPop[u] for u in e) for e in enclaveLists],label=\"enclave 1 pop\",histtype='step')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "463db75a-694e-4c7d-9693-e10f3b4d65db",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Before addressing enclaves, let's triage the discontinuous HDs\n",
      "Now work on dropping smallish disconnected pieces that would keep us above 735378 district pop vs 774082 target\n",
      "we'll also trim any HD with total islands' pop <= 15481\n",
      "working on HD 1542\n",
      "Out of 24 discontig HDs 24 had discontig HDs.\n",
      "Of these, 3 won't be under 735378 after all minor discontigys were shed, while 21 would be too underpopped if we trimmed the discontig pieces\n",
      "here is adjusted pop by original pop for those we trimmed and those we didn't (x)\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, reclassify after the trimming\n",
      "There are 21 HDs still with both discontinuity problems\n",
      "Additionally, 0 of the originally discontig HDs are now contig but still have an enclave\n"
     ]
    }
   ],
   "source": [
    "print(\"Before addressing enclaves, let's triage the discontinuous HDs\")\n",
    "#this is the CANTRIM code####\n",
    "\n",
    "#for t in sPgenerator:\n",
    "#    isContig, smallP = isContiguous(filledHDvtdList[t],unitNbrs)\n",
    "#    if isContig:\n",
    "#        print(\"oops!\",t)\n",
    "maxNudgeDownPop = int(0.02 * aDP)\n",
    "minPostFixPop = int(0.95 * aDP)\n",
    "print(\"Now work on dropping smallish disconnected pieces that would keep us above\",minPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "print(\"we'll also trim any HD with total islands' pop <=\",maxNudgeDownPop)\n",
    "nOrigIslands = [0 for t in range(nHDs)]\n",
    "totalIslandPop = [0. for t in range(nHDs)]\n",
    "tryToTrim, canTrim, cantTrim = list(), list(), list()\n",
    "for jj, t in enumerate(sPgenerator):\n",
    "    if jj%100 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    currList, shedList, shedPop = HDunitList[t].copy(), list(),  0.\n",
    "    done,newList = isContiguous(currList,unitNbrs)\n",
    "    if not done:\n",
    "        tryToTrim.append(t)\n",
    "        while not done:\n",
    "            shedList += newList\n",
    "            shedPop += np.sum( [unitPop[u] for u in newList] )\n",
    "            currList = list (  set(currList).difference(set(newList ))  )\n",
    "            done, newList = isContiguous(currList, unitNbrs)\n",
    "            nOrigIslands[t] +=1\n",
    "            \n",
    "        totalIslandPop[t] = shedPop            \n",
    "        if shedPop <= maxNudgeDownPop or HDvPop[t] - shedPop >= minPostFixPop:\n",
    "            canTrim.append(t)\n",
    "            HDvPop[t] -= shedPop\n",
    "            HDunitList[t] = list (set(HDunitList[t]).difference(set(shedList)) )\n",
    "        else:\n",
    "            cantTrim.append(t)\n",
    "print(\"Out of\",len(sPgenerator),\"discontig HDs\",len(tryToTrim),\"had discontig HDs.\")\n",
    "print(\"Of these,\",len(canTrim),\"won't be under\",minPostFixPop,\"after all minor discontigys were shed, while\",\n",
    "      len(cantTrim),\"would be too underpopped if we trimmed the discontig pieces\")\n",
    "plt.scatter([HDvPop[t] + totalIslandPop[t] for t in canTrim],[HDvPop[t] for t in canTrim])\n",
    "plt.scatter([HDvPop[t]                     for t in cantTrim],[HDvPop[t] for t in cantTrim],marker=\"x\")\n",
    "print(\"here is adjusted pop by original pop for those we trimmed and those we didn't (x)\")\n",
    "plt.plot([0.9*aDP, 1.1*aDP],[aDP, aDP], ls=\"--\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Now, reclassify after the trimming\")\n",
    "badDiscoList, stillHasEnclave = list(), list()\n",
    "for t in sPgenerator:    \n",
    "    unbroken, noEnclave, __, ____ = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if not unbroken:\n",
    "        badDiscoList.append(t)  #will do a major triage on these later\n",
    "    if unbroken and not noEnclave:\n",
    "        stillHasEnclave.append(t)\n",
    "print(\"There are\",len(badDiscoList),\"HDs still with both discontinuity problems\")\n",
    "print(\"Additionally,\",len(stillHasEnclave),\"of the originally discontig HDs are now contig but still have an enclave\")\n",
    "eLgenerator += stillHasEnclave"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "39d37c15-759f-462c-b503-047b6b5e1554",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "77 447 21\n",
      "{6155, 6162, 21, 6170, 36, 4132, 4136, 41, 4148, 4155, 4089, 97, 2147, 4217, 4232, 4238, 2206, 164, 6322, 178, 6327, 4284, 4301, 227, 4324, 238, 251, 2300, 2301, 255, 2303, 2304, 2305, 2306, 2307, 4352, 4355, 269, 274, 275, 2323, 2326, 2327, 2329, 2332, 284, 2333, 288, 2341, 2344, 2345, 302, 306, 2358, 2359, 4406, 2360, 321, 2372, 2373, 2374, 2375, 2376, 2381, 336, 2385, 2387, 2388, 2403, 2404, 2412, 2413, 370, 382, 390, 398, 411, 4510, 4515, 4518, 4519, 4535, 4536, 4547, 4548, 4553, 458, 4564, 474, 4577, 4581, 494, 511, 4612, 528, 535, 538, 4639, 545, 562, 563, 570, 573, 4678, 4697, 4698, 4699, 4702, 4703, 610, 615, 4712, 4716, 621, 628, 4733, 643, 4741, 4742, 648, 4747, 4748, 663, 669, 678, 694, 4795, 4798, 4799, 4800, 4801, 4802, 4803, 4804, 4805, 4806, 711, 4807, 4808, 4809, 4813, 720, 4816, 722, 723, 724, 725, 728, 729, 4827, 733, 4833, 738, 744, 745, 746, 747, 748, 750, 754, 756, 762, 2813, 4866, 4867, 783, 2836, 2838, 2843, 4891, 2844, 797, 804, 2854, 2855, 808, 4905, 2856, 2857, 811, 4904, 813, 2861, 2866, 819, 2871, 824, 825, 827, 829, 2879, 833, 2882, 835, 2885, 4936, 841, 846, 848, 849, 852, 855, 4954, 859, 869, 870, 876, 880, 881, 4977, 883, 4980, 4981, 886, 4984, 4985, 893, 4989, 896, 897, 901, 902, 4997, 4998, 4999, 906, 5002, 908, 913, 914, 917, 921, 5022, 932, 934, 941, 945, 5046, 959, 961, 5057, 964, 5060, 965, 5061, 5062, 969, 970, 5068, 5071, 5072, 988, 989, 5088, 998, 999, 5098, 1004, 5100, 5101, 1013, 1015, 5113, 1025, 5123, 1029, 1038, 1040, 5141, 1047, 1051, 1067, 1070, 1076, 1081, 1083, 5179, 1089, 5186, 5187, 1095, 1096, 1097, 1099, 5195, 5196, 5197, 5199, 5200, 1107, 1110, 1112, 1119, 1131, 5228, 5229, 5231, 1136, 5232, 5234, 5235, 1140, 5237, 1145, 1148, 5245, 1151, 5247, 5258, 5260, 1168, 1169, 1171, 5272, 5273, 5282, 5283, 5284, 5285, 5291, 5295, 5296, 5302, 5303, 5305, 5306, 5307, 5308, 5313, 1218, 5314, 1220, 5315, 5322, 5323, 5329, 5330, 5332, 5338, 5339, 5342, 5344, 5349, 5353, 5354, 5359, 5366, 5372, 5373, 3326, 5376, 5377, 5378, 5379, 5388, 5391, 3345, 1298, 3347, 5396, 3349, 1303, 1304, 5399, 1312, 1337, 1339, 5443, 5445, 1350, 1351, 5447, 1353, 1354, 1355, 1358, 5454, 1360, 5455, 5459, 1365, 5463, 5468, 1374, 5473, 1378, 1379, 5474, 5476, 5478, 1388, 1399, 1400, 1405, 1409, 1410, 1414, 1420, 1421, 1422, 1425, 1433, 5574, 1482, 1492, 1500, 1503, 1507, 5605, 1510, 1511, 1512, 1515, 1517, 1519, 1522, 1527, 1544, 1545, 1546, 1551, 5648, 1559, 1573, 1574, 1577, 1578, 1579, 1580, 1586, 1587, 1589, 1590, 1592, 5688, 1594, 1595, 3650, 5698, 3653, 1612, 5709, 3664, 3665, 1618, 3666, 5716, 1625, 3674, 3676, 5725, 3678, 3679, 3685, 5735, 3688, 5744, 5747, 3702, 3703, 3705, 3714, 3721, 1678, 1679, 5775, 5778, 3731, 3733, 3735, 5786, 3743, 3744, 5797, 5803, 1713, 1714, 5836, 1742, 5842, 5844, 5845, 1753, 5850, 5855, 1763, 3819, 3824, 3827, 5883, 5884, 5886, 1793, 1804, 5943, 5951, 5955, 6004, 6064, 6080, 6130, 6133, 2041}\n"
     ]
    }
   ],
   "source": [
    "print(len(discontigOnly),len(bothProblems), len(badDiscoList))\n",
    "print((set(discontigOnly).union(set(bothProblems)) ) .difference(set(badDiscoList)) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "2e54bac4-c327-473d-bbb4-257486bddd20",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "And now, the major disco'd HDs (< 0.75 aDP in HDcP-contig portion and/or enclaves).  Redraw fully using HDswell\n",
      "Assuming we have run the previous canSwell block.  This block repeats the code, but starting from the home unit\n",
      "This takes 1 - 1000 sec per HD :-( The total number of HDs to fix is 21\n",
      "swell-generating HD 1542 our 1 th HD we must regrow out of 21 0 sec elapsed\n",
      "swell-generating HD 2384 our 11 th HD we must regrow out of 21 71 sec elapsed\n",
      "swell-generating HD 6113 our 21 th HD we must regrow out of 21 87 sec elapsed\n"
     ]
    }
   ],
   "source": [
    "#THIS IS THE MUSTSPAWN code block\n",
    "print(\"And now, the major disco'd HDs (< 0.75 aDP in HDcP-contig portion and/or enclaves).  Redraw fully using HDswell\")\n",
    "print(\"Assuming we have run the previous canSwell block.  This block repeats the code, but starting from the home unit\")\n",
    "print(\"This takes 1 - 1000 sec per HD :-( The total number of HDs to fix is\",len(badDiscoList))\n",
    "avgDiam = MAP.area**0.5 / float(nDistricts)\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(badDiscoList):\n",
    "    if i%10 == 0:\n",
    "        print(\"swell-generating HD\",t,\"our\",i+1,\"th HD we must regrow out of\",len(badDiscoList),int(time.time()-startTime),\"sec elapsed\" )\n",
    "    notInCluster = True\n",
    "    for jj, geo in enumerate(CCBgeom):  #swell in-corner HDs from the corner cluster\n",
    "        if geo.contains(hdCP[t]):\n",
    "            starterU = allUnits.index(jj+0.25)\n",
    "            notInCluster = False\n",
    "    if notInCluster:\n",
    "        distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "        starterU = HDunitList[t][distList.index(np.min(distList))]  #starter = unit with centroid closest to the hd center\n",
    "    contigUs = [starterU]  #we used getContigFromStarter(starterU, HDvtdList[t], unitNbrs) in above code block\n",
    "    contigPop = np.sum( [ unitPop[u] for u in contigUs ] )\n",
    "    gap = aDP - contigPop\n",
    "    origGap = gap\n",
    "    currList, addedList = contigUs.copy(), list()\n",
    "    adjoiners = getAdjoiners(currList, unitNbrs)\n",
    "    nearHDlist = [uu for uu in adjoiners]  #bias toward underused, close to HD (and its center)\n",
    "    nearHDscore = [ (0.2*(unitUse[uu] - 1.) ) + 0.5*(unitCP[uu].distance(HDpoly[t]) + \n",
    "        unitCP[uu].distance(hdCP[t])  )  / HDdiam[t] for uu in adjoiners ]\n",
    "    stillGoing = True\n",
    "    \n",
    "    while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "        while i < len(nearHDscore) and notYetPicked:        \n",
    "            listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "            unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "            canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "            if canAdd:\n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else: #we selected the best unit to add legally\n",
    "            gap -= unitPop[unitNoToAdd]\n",
    "            addedList.append(unitNoToAdd)\n",
    "            currList.append( unitNoToAdd)\n",
    "            for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap:  \n",
    "                    nearHDlist.append(uu)\n",
    "                    nearHDscore.append((0.1*(unitUse[uu] - 1.) ) + 0.5*(unitCP[uu].distance(HDpoly[t]) + \n",
    "                                                                        unitCP[uu].distance(hdCP[t])  )  / HDdiam[t] )\n",
    "            del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "            del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "            for i, uu in enumerate(nearHDlist.copy()):\n",
    "                if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                    del nearHDscore[nearHDlist.index(uu)]\n",
    "                    del nearHDlist[ nearHDlist.index(uu)]\n",
    "    for u in addedList:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    for u in list( set(HDunitList[t]).difference(set(contigUs)) ):\n",
    "        unitUse[u] -= HDweight[t] * nDistricts       \n",
    "    HDunitList[t] = contigUs + addedList\n",
    "    HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "    HDnAddedUnits[t] = len(addedList)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "b78199da-ac7c-4cfb-ac0b-26363a8a8c56",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "prev avg use and its sd are 1.00319 0.10168\n",
      "defining and displaying current unit use after most recent manipulations; compare to original farther above.\n",
      "current avg use and its sd are 1.00317 0.10233\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"prev avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "print(\"defining and displaying current unit use after most recent manipulations; compare to original farther above.\")\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "a2242181-3a07-40b7-ae56-bbe47bd2dc79",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(not-so-)final check -- any more disco's ?\n",
      "working on HD 0 time is now 0 sec\n",
      "working on HD 500 time is now 11 sec\n",
      "working on HD 1000 time is now 24 sec\n",
      "working on HD 1501 time is now 30 sec\n",
      "working on HD 2002 time is now 40 sec\n",
      "working on HD 2503 time is now 59 sec\n",
      "working on HD 3003 time is now 67 sec\n",
      "working on HD 3503 time is now 73 sec\n",
      "working on HD 4003 time is now 81 sec\n",
      "working on HD 4503 time is now 85 sec\n",
      "working on HD 5003 time is now 96 sec\n",
      "working on HD 5504 time is now 107 sec\n",
      "working on HD 6004 time is now 113 sec\n",
      "out of 6356 total HDs, there were 6321 0 35 0 HDs that were clean, discontig only, enclave-only, both problems after triage\n",
      "this took 115 seconds with maxLoop =  5\n"
     ]
    }
   ],
   "source": [
    "print(\"(not-so-)final check -- any more disco's ?\")\n",
    "maxLOOP = 5  #can increase to avoid false enclave detection\n",
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%500 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime),\"sec\")\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs, maxLOOP)\n",
    "    if not noEnclave:\n",
    "        noEnclave, enclaveList = isContiguous(list({u for u in range(nUnits)}.difference(set(HDunitList[t]))),unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems after triage\")\n",
    "print(\"this took\",int(time.time() - startTime),\"seconds with maxLoop = \", maxLOOP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "623fb818-67d9-458d-b854-4c70dfa449ce",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, let's fill in all enclaves that won't put us over 812786 district pop vs 774082 target\n",
      "working on enclave-y HD 251 . We have evaluated 0 of 4967 enclavy HDs.Time is now 0\n",
      "Out of 4967 HDs with enclaves 35 had enclaves.\n",
      "Of these, 35 wouldn't be over 812786 if all enclaves filled, while 0 were too populous\n",
      "here is enclave pop by final pop for those we filled\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#OPTIONAL if still enclaves -- rerun the CANFILL CODE  #check if sum of enclave pops small enough to add\n",
    "maxNudgeUpPop = int(0.02 * aDP)\n",
    "maxPostFixPop = int(1.05 * aDP)\n",
    "print(\"Now, let's fill in all enclaves that won't put us over\",maxPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "nOrigEnclaves = [0 for t in range(nHDs)]\n",
    "totalEnclavePop = [0. for t in range(nHDs)]\n",
    "tryToFill, canFill, cantFill = list(), list(), list()\n",
    "startTime = time.time()  #takes about xx sec per HD triage\n",
    "        \n",
    "for iii, t in enumerate(enclaveOnly):  #internals + edgers):\n",
    "    if iii%100 == 0:\n",
    "        print(\"working on enclave-y HD\",t,\". We have evaluated\",iii,\"of\",len(internals+edgers),\"enclavy HDs.Time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and not noEnclave:  #\"and unbroken\" new 1/15 - discontig HDs will usually appear to have enclaves.  We'll fix these in later block\n",
    "        tryToFill.append(t)\n",
    "        enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "        nOrigEnclaves[t] = len(enclaveLists)\n",
    "        totalEnclavePop[t] = np.sum( [ [np.sum([unitPop[u] for u in eL])] for eL in enclaveLists ] ) \n",
    "        if HDvPop[t] + totalEnclavePop[t] <= maxPostFixPop or totalEnclavePop[t] < maxNudgeUpPop:\n",
    "            canFill.append(t)\n",
    "            for eL in enclaveLists:\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += np.sum([unitPop[u] for u in eL])\n",
    "        else:\n",
    "            cantFill.append(t)\n",
    "print(\"Out of\",len(internals+edgers),\"HDs with enclaves\",len(tryToFill),\"had enclaves.\")\n",
    "print(\"Of these,\",len(canFill),\"wouldn't be over\",maxPostFixPop,\"if all enclaves filled, while\",len(cantFill),\"were too populous\")\n",
    "plt.scatter([HDvPop[t] for t in canFill],[totalEnclavePop[t] for t in canFill])\n",
    "print(\"here is enclave pop by final pop for those we filled\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "18f46c40-7f28-4714-962f-0b462ff97b8a",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final ??? check -- any more disco's ?\n",
      "working on HD 0 time is now 0 sec\n",
      "working on HD 500 time is now 4 sec\n",
      "working on HD 1000 time is now 8 sec\n",
      "working on HD 1501 time is now 11 sec\n",
      "working on HD 2002 time is now 15 sec\n",
      "working on HD 2503 time is now 19 sec\n",
      "working on HD 3003 time is now 24 sec\n",
      "working on HD 3503 time is now 27 sec\n",
      "working on HD 4003 time is now 32 sec\n",
      "working on HD 4503 time is now 36 sec\n",
      "working on HD 5003 time is now 39 sec\n",
      "working on HD 5504 time is now 43 sec\n",
      "working on HD 6004 time is now 47 sec\n",
      "out of 6356 total HDs, there were 6356 0 0 0 HDs that were clean, discontig only, enclave-only, both problems after triage\n",
      "this took 49 seconds with maxLoop =  5\n"
     ]
    }
   ],
   "source": [
    "print(\"final ??? check -- any more disco's ?\")  #run again if we ran above block to fill minor enclaves\n",
    "maxLOOP = 5  #can increase to avoid false enclave detection\n",
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%500 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime),\"sec\")\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs, maxLOOP)\n",
    "    if not noEnclave:\n",
    "        noEnclave, enclaveList = isContiguous(list({u for u in range(nUnits)}.difference(set(HDunitList[t]))),unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems after triage\")\n",
    "print(\"this took\",int(time.time() - startTime),\"seconds with maxLoop = \", maxLOOP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "de4d8af8-cc64-4215-9b95-f4c6a2bd03af",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "savedAgainUnitList = [HDunitList[t].copy() for t in range(nHDs)] #safekeeping    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "f4bb76c7-0ae0-40cb-9c6a-ee436dfc30c4",
   "metadata": {
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [],
   "source": [
    "HDunitList = [savedAgainUnitList[t].copy() for t in range(nHDs)]  #restart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "f3bcd6a8-40b6-4764-a0d1-6814e3286cb8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking on our corner clusters and unit county usage\n",
      "usage, unit no, unit pop, type (0.5 = unit county, 0.25 = cluster) ...\n",
      "0.99557     6197     95263 0.25\n",
      "0.97617     6198     64837 0.25\n"
     ]
    }
   ],
   "source": [
    "print(\"checking on our corner clusters and unit county usage\")\n",
    "print(\"usage, unit no, unit pop, type (0.5 = unit county, 0.25 = cluster) ...\")\n",
    "for u in range(nUnits):\n",
    "    if int(allUnits[u]) != allUnits[u] :\n",
    "        print(r5(unitUse[u]),\"   \",u,\"   \",int(unitPop[u]), allUnits[u]%1 )\n",
    "# note for MN, option 3 here led to tight CCB unit usage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "1e983c03-777a-4e81-bed0-34a620175f83",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "let's visualize over-used and underused units, < 0.75 or > 1.25\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and here is the histogram of HD pops\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "minUnitUse, maxUnitUse = 0.75, 1.25\n",
    "print(\"let's visualize over-used and underused units, <\",minUnitUse,\"or >\",maxUnitUse)\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < minUnitUse:\n",
    "        plotPoly(unitGeom[u],0.2)\n",
    "        plotCenter(\"u\",unitCP[u])\n",
    "    if unitUse[u] > maxUnitUse:\n",
    "        plotPoly(unitGeom[u], 1.5)\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()\n",
    "print(\"and here is the histogram of HD pops\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist],bins = [0, 0.6*aDP, 0.7*aDP, 0.85*aDP, 0.9*aDP, 0.95*aDP,\n",
    "         0.98*aDP, aDP, 1.02*aDP, 1.05*aDP, 1.1*aDP, 1.15*aDP, 1.3*aDP, 1.5*aDP, 2.0*aDP])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "9bc31b5a-992d-4a38-b9fe-3470b55e1e2e",
   "metadata": {},
   "outputs": [],
   "source": [
    "HDvPop = [0. for t in range(nHDs)]\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"opt3ContigButOffPopUnit.csv\" #\"contigUnpatchedB.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "7b9b68ef-6ae9-4d80-895d-41a86f48a55f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hi\n"
     ]
    }
   ],
   "source": [
    "print(\"hi\")  #see MN for code to boost any under-used CCBs via border linking strategy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f6150cac-2249-415b-a364-edf55dc441ea",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "114705bb-9640-45f1-9f25-030030efaa63",
   "metadata": {},
   "outputs": [],
   "source": [
    "#below here -- working on tightening use distro while squaring up pop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "5d7d8519-eb3d-4345-9ac6-ab888e61c348",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "before patching, make another copy of the current HD lists\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pre-patch avg use and its sd are 1.0032 0.1023\n"
     ]
    }
   ],
   "source": [
    "print(\"before patching, make another copy of the current HD lists\")\n",
    "latestHDlist = [HDunitList[t].copy() for t in range(nHDs)]   #More safekeeping\n",
    "latestHDpop, latestUnitUse = [0. for t in range(nHDs)], [0. for u in range(nUnits)]\n",
    "for t in popHDlist:\n",
    "    for u in latestHDlist[t]:\n",
    "        latestHDpop[t] += unitPop[u]\n",
    "        latestUnitUse[u] += nDistricts * HDweight[t]\n",
    "latestUnitWeights, latestUnitDistro = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if latestUnitUse[u] > 0.1:\n",
    "        latestUnitDistro.append(latestUnitUse[u])\n",
    "        latestUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(latestUnitDistro, weights=latestUnitWeights, bins = 20, histtype = \"step\")\n",
    "plt.show()\n",
    "latestAvg, latestSD = getWeightedAvgAndSD(latestUnitDistro, latestUnitWeights)\n",
    "print(\"pre-patch avg use and its sd are\",r5(latestAvg),r5(latestSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "b1971853-bda7-49a4-9f25-1bdfd5e75aa2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on avg unit-to-HDcp dist for HD 0\n",
      "working on avg unit-to-HDcp dist for HD 800\n",
      "working on avg unit-to-HDcp dist for HD 1601\n",
      "working on avg unit-to-HDcp dist for HD 2403\n",
      "working on avg unit-to-HDcp dist for HD 3203\n",
      "working on avg unit-to-HDcp dist for HD 4003\n",
      "working on avg unit-to-HDcp dist for HD 4803\n",
      "working on avg unit-to-HDcp dist for HD 5604\n"
     ]
    }
   ],
   "source": [
    "avgDist = [0. for t in range(nHDs)]  #about 6sec per 1000 HDs\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%800 == 0:\n",
    "        print(\"working on avg unit-to-HDcp dist for HD\",t)\n",
    "    avgDist[t] =  np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "f5b99900-614a-47df-b7de-5d59fffd6d3a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "before patching, make another copy of the current HD lists\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pre-patch avg use and its sd are 1.0032 0.1023\n"
     ]
    }
   ],
   "source": [
    "#Restart - may want to comment out first line\n",
    "HDunitList = [latestHDlist[t].copy() for t in range(nHDs)]\n",
    "unitUse = [0. for u in range(nUnits) ]\n",
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t] ]) for t in range(nHDs) ]\n",
    "\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse, weights = unitPop,bins = 50)\n",
    "plt.show()\n",
    "plt.hist([HDvPop[t] for t in popHDlist], bins=50)\n",
    "plt.show()\n",
    "print(\"before patching, make another copy of the current HD lists\")\n",
    "latestHDlist = [HDunitList[t].copy() for t in range(nHDs)]   #More safekeeping\n",
    "latestHDpop, latestUnitUse = [0. for t in range(nHDs)], [0. for u in range(nUnits)]\n",
    "for u in range(nUnits):\n",
    "    if latestUnitUse[u] > 0.1:\n",
    "        latestUnitDistro.append(latestUnitUse[u])\n",
    "        latestUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(latestUnitDistro, weights=latestUnitWeights, bins = 20, histtype = \"step\")\n",
    "plt.show()\n",
    "latestAvg, latestSD = getWeightedAvgAndSD(latestUnitDistro, latestUnitWeights)\n",
    "print(\"pre-patch avg use and its sd are\",r5(latestAvg),r5(latestSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "27b51cd0-8bb6-4b16-bb79-37498e59ce5c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We will now square up the 211 HDs with pop < 766342 to within 1203\n",
      "working on squaring up HD 15 time is now 0\n",
      "working on squaring up HD 2403 time is now 27\n",
      "working on squaring up HD 6177 time is now 62\n",
      "We have addressed underpop in a total of 211 HDs\n",
      "Here is a scatterplot of original (x) to final pop (y)\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#SQUARING UP UNDERPOPPED\n",
    "HDnAddedUnits, HDaddedPop = [0]*nHDs, [0.]*nHDs\n",
    "underPoppedList = list()\n",
    "minDistrictPop, maxDistrictPop = 0.99 * aDP, 1.01 * aDP\n",
    "for t,pop in enumerate(HDvPop):\n",
    "    if pop < minDistrictPop and t in popHDlist:\n",
    "        underPoppedList.append(t)\n",
    "print(\"We will now square up the\",len(underPoppedList),\"HDs with pop <\",int(minDistrictPop),\"to within\",int(maxGap) )\n",
    "startTime = time.time()\n",
    "maxGap = 0.9 * np.median(unitPop) \n",
    "for ii,t in enumerate(underPoppedList):\n",
    "    if ii%100 == 0:\n",
    "        print(\"working on squaring up HD\",t,\"time is now\",int(time.time() - startTime)) \n",
    "    gap = aDP - HDvPop[t]\n",
    "    origGap = gap\n",
    "    nearHDlist, nearHDscore = list(), list()  #these will be dynamic lists of the nearby underused units\n",
    "    for u in HDunitList[t]:\n",
    "        for uu in unitNbrs[u]:\n",
    "            if uu not in HDunitList[t] and uu not in nearHDlist and unitPop[uu] < gap + maxGap:\n",
    "                nearHDlist.append(uu)   #below line: bias toward close, underused\n",
    "                nearHDscore.append((unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )  \n",
    "    currList = HDunitList[t].copy()\n",
    "    addedList = list()\n",
    "    stillGoing = True\n",
    "    while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "        while i < len(nearHDscore) and notYetPicked:        \n",
    "            listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "            unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "            canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "            if canAdd: \n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else:\n",
    "            gap -= unitPop[unitNoToAdd]\n",
    "            addedList.append(unitNoToAdd)\n",
    "            currList.append( unitNoToAdd)\n",
    "            for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap:  \n",
    "                    nearHDlist.append(uu)\n",
    "                    nearHDscore.append((unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )  #bias toward close, underused\n",
    "            del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "            del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "            for i, uu in enumerate(nearHDlist.copy()):\n",
    "                if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                    del nearHDscore[nearHDlist.index(uu)]\n",
    "                    del nearHDlist[ nearHDlist.index(uu)]\n",
    "    for u in addedList:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    HDunitList[t] += addedList\n",
    "    HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "    HDnAddedUnits[t] = len(addedList)\n",
    "    HDaddedPop[t] = np.sum( [unitPop[u] for u in addedList] )\n",
    "    if HDvPop[t] > maxDistrictPop:\n",
    "        print(\"Oops! HD\",t,\"now has overshot pop =\",int(HDvPop[t]),\"not\",int(aDP),\"after adding\",HDaddedPop[t] )\n",
    "print(\"We have addressed underpop in a total of\",len(underPoppedList),\"HDs\")\n",
    "print(\"Here is a scatterplot of original (x) to final pop (y)\")\n",
    "plt.scatter([HDvPop[t] - HDaddedPop[t] for t in underPoppedList], [HDvPop[t] for t in underPoppedList])\n",
    "plt.axhline(y=aDP, xmin = 0.9*aDP, xmax = 1.1*aDP, ls=\"--\")\n",
    "plt.axvline(x=aDP, ymin = 0.9*aDP, ymax = 1.1*aDP, ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "bc01409d-d9e4-43a6-9fae-c76aa7bdc855",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "previous unit avg and sd usage are 1.0032 0.1023\n",
      "amped unit avg and sd usage are 1.00452 0.10171\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "prevUnitUse = [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in latestHDlist[t]:\n",
    "        prevUnitUse[u] += HDweight[t] * nDistricts\n",
    "\n",
    "ampedUnitUse = [0. for u in range(nUnits)]\n",
    "ampedHDlist = [HDunitList[t].copy() for t in range(nHDs)]\n",
    "ampedHDpop = [HDvPop[t] for t in range(nHDs) ]\n",
    "for t in popHDlist:\n",
    "    for u in ampedHDlist[t]:\n",
    "        ampedUnitUse[u] += HDweight[t] * nDistricts   #KISS - recalc these\n",
    "plt.hist(prevUnitUse,bins=50,weights=unitPop,label=\"previous\",histtype=\"step\")\n",
    "plt.hist(ampedUnitUse, bins=50, weights=unitPop,label=\"amped\",histtype=\"step\")\n",
    "plt.legend()\n",
    "ampedUnitUseAvg, ampedUnitUseSD = getWeightedAvgAndSD(ampedUnitUse,unitPop)\n",
    "print(\"previous unit avg and sd usage are\",r5(latestAvg), r5(latestSD) )\n",
    "print(\"amped unit avg and sd usage are\",r5(ampedUnitUseAvg), r5(ampedUnitUseSD) )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "ee512b2b-4daa-4a6b-9452-e8dfdfdebc88",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the current barredJettisonSet (usually CCB's) is {6197, 6198}\n"
     ]
    }
   ],
   "source": [
    "#CHECK ON BARRED JETTISON SET BEFORE RUNNING BELOW\n",
    "print(\"the current barredJettisonSet (usually CCB's) is\",barredJettisonSet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "dd7d9818-344c-4150-917b-57a4ee051c92",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing with narrowing the distro.  This loop: remove overused units from overpopped HDs\n",
      "Let's now square down the 588 overPopped HDs to within 1203\n",
      "working on squaring down HD 4 time is now 0\n",
      "working on squaring down HD 1846 time is now 12\n",
      "working on squaring down HD 1908 time is now 24\n",
      "working on squaring down HD 2204 time is now 40\n",
      "working on squaring down HD 4441 time is now 50\n",
      "working on squaring down HD 4849 time is now 61\n",
      "working on squaring down HD 5348 time is now 73\n",
      "working on squaring down HD 5965 time is now 84\n",
      "working on squaring down HD 6081 time is now 99\n",
      "working on squaring down HD 6250 time is now 111\n",
      "We have addressed overpop in a total of 588 HDs\n",
      "Here is a scatterplot of original to final pop\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#SQUARING DOWN\n",
    "print(\"Continuing with narrowing the distro.  This loop: remove overused units from overpopped HDs\")\n",
    "#HDunitList = [ampedHDlist[t].copy() for t in range(nHDs)]\n",
    "#HDvPop =     [ampedHDpop[t]         for t in range(nHDs)]\n",
    "#unitUse =    [ampedUnitUse[u]       for u in range(nUnits)] #saving in case I need to re-run\n",
    "HDnShedUnits = [0]*nHDs\n",
    "overPoppedList = list()\n",
    "startTime = time.time()\n",
    "for t,pop in enumerate(HDvPop):\n",
    "    if pop > maxDistrictPop and t in popHDlist:\n",
    "        overPoppedList.append(t)\n",
    "\n",
    "maxGap = 0.9 * np.median(unitPop)   \n",
    "print(\"Let's now square down the\",len(overPoppedList),\"overPopped HDs to within\", int(maxGap))   \n",
    "for ii,t in enumerate(overPoppedList):\n",
    "    if ii%60 == 0:\n",
    "        print(\"working on squaring down HD\",t,\"time is now\",int(time.time()-startTime))\n",
    "    unbroken, noEnclave, sPL, ePL = enclaveCheck(HDunitList[t],unitNbrs)\n",
    "    if not (unbroken and noEnclave):\n",
    "        print(\"SKIPPING shedding attempt on overpopped HD\",t,\"with pop\",HDvPop[t],\"because it was not legal to start\")\n",
    "    else:\n",
    "        #avgDist = np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]\n",
    "        excess = HDvPop[t] - aDP\n",
    "        origExcess = excess\n",
    "        HDboundaryList, HDboundaryScore = list(), list()  #these will be dynamic lists of the overused border units to jettison\n",
    "        distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "        starterU = HDunitList[t][distList.index(np.min(distList))]\n",
    "        barredSet = barredJettisonSet  #new 4/10/24 for MN, ban CCB jettisoning from ALL HD's, not just near ones\n",
    "        #barredSet = set(get2nbrs([starterU],unitNbrs)).union(barredJettisonSet)  #weaker specification - must be close to be barred\n",
    "\n",
    "        for u in set(HDunitList[t]).difference(barredSet):\n",
    "            isBoundary = False\n",
    "            for uu in unitNbrs[u]:\n",
    "                if uu not in HDunitList[t]:\n",
    "                    isBoundary = True\n",
    "                    break\n",
    "            if isBoundary and HDvPop[t] - unitPop[u] > aDP - maxGap:  #shedding this unit won't send us too far under targetpop\n",
    "                HDboundaryList.append(u)\n",
    "                HDboundaryScore.append((1. - unitUse[u]) - unitCP[u].distance(hdCP[t]) / avgDist[t])  #low-score = bias toward far, overused\n",
    "        currList = HDunitList[t].copy()\n",
    "        shedList, stillGoing = list(), True\n",
    "        while excess > maxGap and len(HDboundaryList) > 0 and stillGoing:   #shed the highest-scoring neighboring overused unit until we've roughly squared the HDpop\n",
    "            idx, i, notYetPicked = np.argsort(HDboundaryScore), 0, True\n",
    "            while i < len(HDboundaryScore) and notYetPicked and stillGoing:        \n",
    "                listNo = idx[i]   #low (large negative) score is preferred to shed\n",
    "                unitNoToShed = HDboundaryList[listNo]  # attempt to shed this unit ...\n",
    "                tryList = list(set(currList).difference( {unitNoToShed} ) )\n",
    "                unbroken, noEnclave, sPL, ePL = enclaveCheck(tryList,unitNbrs) \n",
    "                if unbroken and noEnclave:             #... if that won't eff up contiguity\n",
    "                    notYetPicked = False\n",
    "                else:\n",
    "                    i +=1\n",
    "            if notYetPicked:\n",
    "                stillGoing = False  #can't drop any more units without creating an enclave\n",
    "                print(\"can't drop any more units to HD\",t,\"without creating an enclave\")\n",
    "            else: #add this eligible unit\n",
    "                shedList.append(unitNoToShed)\n",
    "                excess -= unitPop[unitNoToShed]        \n",
    "                del currList[currList.index(unitNoToShed) ]\n",
    "                del HDboundaryList[listNo]\n",
    "                del HDboundaryScore[listNo]\n",
    "                for u in unitNbrs[unitNoToShed]:      # ... and ID any neighboring units that will now be on boundary after we shed this unit\n",
    "                    if u in currList and u not in HDboundaryList and (unitPop[u] <= excess + maxGap and\n",
    "                                                                      u not in barredSet): \n",
    "                        HDboundaryList.append(u)\n",
    "                        HDboundaryScore.append( (1. - unitUse[u]) - unitCP[u].distance(hdCP[t]) / avgDist[t] )  #low-score, bias toward far & overused       \n",
    "                for uu in HDboundaryList.copy():\n",
    "                    if unitPop[uu] > excess + maxGap:  #checking to see if the latest pop change DQ's any large units on current boundary\n",
    "                        del HDboundaryScore[HDboundaryList.index(uu)]\n",
    "                        del HDboundaryList[HDboundaryList.index(uu)]   \n",
    "        for u in shedList:\n",
    "            unitUse[u] -= HDweight[t] * nDistricts\n",
    "        HDunitList[t], HDvPop[t] = currList.copy(), np.sum( [unitPop[u] for u in currList ] )    \n",
    "        if HDvPop[t] < minDistrictPop:\n",
    "            print(\"Oops! HD\",t,\"now has undershot pop =\",int(HDvPop[t]),\"not\",int(aDP),\"after shedding\",\n",
    "                 np.sum([unitPop[u] for u in shedList]) )\n",
    "\n",
    "        HDnShedUnits[t] = -1 * len(shedList)\n",
    "\n",
    "print(\"We have addressed overpop in a total of\",len(overPoppedList),\"HDs\")\n",
    "print(\"Here is a scatterplot of original to final pop\")\n",
    "plt.scatter([ampedHDpop[t] for t in overPoppedList], [HDvPop[t] for t in overPoppedList])\n",
    "plt.axhline(aDP, 0.9*aDP, 1.1*aDP, ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "9a19b23e-43cc-4609-9ee7-6d1057a7a9e1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here are the stats prior to any equi-pop patching\n",
      "amped unit avg and sd usage are 1.00452 0.10171\n",
      "shed unit avg and sd usage are 1.00096 0.09746\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and here are the final populations\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 0 out of 6361\n",
      "working on HD 300 out of 6361\n",
      "working on HD 600 out of 6361\n",
      "working on HD 900 out of 6361\n",
      "working on HD 1200 out of 6361\n",
      "working on HD 1501 out of 6361\n",
      "working on HD 1801 out of 6361\n",
      "working on HD 2103 out of 6361\n",
      "working on HD 2403 out of 6361\n",
      "working on HD 2703 out of 6361\n",
      "working on HD 3003 out of 6361\n",
      "working on HD 3303 out of 6361\n",
      "working on HD 3603 out of 6361\n",
      "working on HD 3903 out of 6361\n",
      "working on HD 4203 out of 6361\n",
      "working on HD 4503 out of 6361\n",
      "working on HD 4803 out of 6361\n",
      "working on HD 5103 out of 6361\n",
      "working on HD 5404 out of 6361\n",
      "working on HD 5704 out of 6361\n",
      "working on HD 6004 out of 6361\n",
      "working on HD 6305 out of 6361\n",
      "all done checking HD and complement contiguity for all 6361 HDs\n",
      "underpop contigFail, enclaveFail = 0 0 out of 211\n",
      "overpop contigFail, enclaveFail = 0 0 out of 588\n",
      "total contigFail, enclaveFail =  0 0\n",
      "CCB unit 6197 with pop 95263.0 now has use 0.99557\n",
      "CCB unit 6198 with pop 64837.0 now has use 0.97617\n"
     ]
    }
   ],
   "source": [
    "print(\"Here are the stats prior to any equi-pop patching\")\n",
    "shedUnitUse = [0. for u in range(nUnits)]\n",
    "shedHDlist = [HDunitList[t].copy() for t in range(nHDs)]\n",
    "shedHDpop = [HDvPop[t] for t in range(nHDs) ]\n",
    "for t in popHDlist:\n",
    "    for u in shedHDlist[t]:\n",
    "        shedUnitUse[u] += HDweight[t] * nDistricts   #KISS - recalc these\n",
    "#plt.hist(latestUnitUse,bins=50,weights=unitPop,label=\"pre-squaring\",histtype=\"step\")\n",
    "plt.hist(ampedUnitUse, bins=50, weights=unitPop,label=\"amped\",histtype=\"step\")\n",
    "plt.hist(shedUnitUse, bins=50, weights=unitPop,label=\"shed\",histtype=\"step\")\n",
    "plt.legend()\n",
    "#latestAvg, latestSD = getWeightedAvgAndSD(latestUnitUse,unitPop)\n",
    "shedUnitUseAvg, shedUnitUseSD = getWeightedAvgAndSD(shedUnitUse,unitPop)\n",
    "#print(\"orig unit avg and sd usage are\",r5(latestAvg), r5(latestSD) )\n",
    "print(\"amped unit avg and sd usage are\",r5(ampedUnitUseAvg), r5(ampedUnitUseSD) )\n",
    "print(\"shed unit avg and sd usage are\", r5(shedUnitUseAvg),  r5(shedUnitUseSD) )\n",
    "plt.show()\n",
    "# note: when I ran this early Jan, went from 0.12662 to 0.09961 to 0.09432 SD orig-amped-shed, but contig not yet done\n",
    "print(\"and here are the final populations\")\n",
    "plt.hist([shedHDpop[t] for t in popHDlist],bins=20)\n",
    "plt.axvline(aDP,ls=\"--\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "failEnclaveSet, failContigSet = set(), set()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%300 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs,5)\n",
    "    if not noEnclave:\n",
    "        noEnclave, eList = isContiguous(list({u for u in range(nUnits)}.difference(set(HDunitList[t]))),unitNbrs)\n",
    "    if not unbroken or not noEnclave:\n",
    "        #print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "        pass\n",
    "    if not unbroken:\n",
    "        failContigSet.add(t)\n",
    "    if not noEnclave:\n",
    "        failEnclaveSet.add(t)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")\n",
    "failContigUnderpopped, failEnclaveUnderpopped = set(underPoppedList).intersection(failContigSet), set(underPoppedList).intersection(failEnclaveSet)\n",
    "failContigOverpopped, failEnclaveOverpopped = set(overPoppedList).intersection(failContigSet), set(overPoppedList).intersection(failEnclaveSet)\n",
    "print(\"underpop contigFail, enclaveFail =\",len(failContigUnderpopped), len(failEnclaveUnderpopped),\"out of\",len(underPoppedList))\n",
    "print(\"overpop contigFail, enclaveFail =\",len(failContigOverpopped), len(failEnclaveOverpopped),\"out of\",len(overPoppedList))\n",
    "print(\"total contigFail, enclaveFail = \",len(failContigSet), len(failEnclaveSet) )\n",
    "for u in range(nUnits):\n",
    "    if abs( allUnits[u]%1 - 0.25) < 0.01:\n",
    "        print(\"CCB unit\",u,\"with pop\",unitPop[u],\"now has use\",r5(unitUse[u]) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "ff3288f1-f9ca-473c-886c-ee8d6c2637bf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6361 6199\n"
     ]
    }
   ],
   "source": [
    "print(nHDs, nUnits)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "id": "af4a9d26-98ab-4ceb-96c1-f2083abcc5d7",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we will remove CCB unit 1647 from HD 962 leaving it with pop 740526.0\n",
      "we will remove CCB unit 1647 from HD 1321 leaving it with pop 715813.0\n",
      "we will remove CCB unit 1648 from HD 1481 leaving it with pop 426197.66490213\n",
      "we will remove CCB unit 1647 from HD 1999 leaving it with pop 738985.0\n"
     ]
    }
   ],
   "source": [
    "#see MD code if we need to remove a stuck CCB's from any HDs and then redo the square-up after dropping them\n",
    "                \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "e7bfa674-8fc8-42c8-86e9-76d334d3c47c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "HDvPop = [0. for t in range(nHDs)]  #writing UNIT lists to a file\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"opt3ContigGoodPop.csv\" #\"contigUnpatchedB.csv\" unpatchedContigGoodPop.csv\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 430,
   "id": "c0c3a3d8-cf79-40ad-aa2e-b6793266f1d4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "prior to patching, write these contiguous lists to a file, converting to vtd lists\n"
     ]
    }
   ],
   "source": [
    "#SKIP THIS FOR STATES WITH FRAGMENTED VTD'S ###########\n",
    "print(\"prior to patching, write these contiguous lists to a file, converting to vtd lists\")\n",
    "tList = [t for t in range(nHDs)]\n",
    "vtdList = [list() for t in range(nHDs)]\n",
    "unitVTDlist = [list() for u in range(nUnits)]\n",
    "for u in range(nUnits):\n",
    "    if allUnits[u] % 1 == 0.5 :\n",
    "        c = int(allUnits[u])\n",
    "        unitVTDlist[u] = countyTractList[c].copy()\n",
    "    if allUnits[u] % 1 == 0.25 :\n",
    "        CCBnumber = int(allUnits[u])\n",
    "        for c in CCBlist[CCBnumber] :\n",
    "            unitVTDlist[u] += countyTractList[c]\n",
    "    if allUnits[u] % 1 == 0:\n",
    "        unitVTDlist[u] = [allUnits[u]]\n",
    "        for i,uu in enumerate(surrounders):\n",
    "            if u == uu:\n",
    "                unitVTDlist[u].append(surroundedVTDs[i])\n",
    "\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        vtdList[t] += unitVTDlist[u]\n",
    "    #add more stuff here to convert to vtd lists\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":vtdList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"needsEnclaveRemoval.csv\" #\"contigUnpatchedB.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "7a36c0ba-5a68-445b-a223-b7fa55dfd728",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are 4110 HD centers\n"
     ]
    }
   ],
   "source": [
    "nHDs = len(vtdGeom)\n",
    "print(\"there are\",nHDs,\"HD centers\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "1b794580-5a58-4238-b310-7c87872ed679",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this optional RESTART block pulls in an existing UNIT (not vtd) list for patching\n",
      "Must have already established unitGeoms, pops, topology -- or read in via next block\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the unpatched UNIT list file, e.g. ./2024state_HD_output/NJ6361opt3ContigGoodPop.csv ./2024state_HD_output/NJ6361opt3ContigGoodPop.csv\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sum of HDweight should be unity, actually is 0.9999999999997714\n",
      "I will now renormalize\n",
      "normalized weight is now 1.0\n",
      "I read in 6361 HD lists of units\n",
      "orig unit avg and sd usage are 1.00096 0.09746\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"this optional RESTART block pulls in an existing UNIT (not vtd) list for patching\") #vtdlist for patching\")\n",
    "print(\"Must have already established unitGeoms, pops, topology -- or read in via next block\")\n",
    "guessedFile = \"enter the unpatched UNIT list file, e.g. ./2024state_HD_output/\"+STATE+str(nHDs)+\"opt3ContigGoodPop.csv\"\n",
    "infile = input(guessedFile)\n",
    "inDF = pd.read_csv(infile)\n",
    "vtdListString = inDF[\"HDunitList\"]  #inDF[\"HDvtdList\"]\n",
    "nHDs = len(vtdListString)\n",
    "inVTDlist = [ast.literal_eval(vtdListString[t]) for t in range(nHDs)]\n",
    "HDweight = inDF[\"HDweight\"]\n",
    "sumWt = np.sum(HDweight)\n",
    "print(\"sum of HDweight should be unity, actually is\",sumWt)\n",
    "print(\"I will now renormalize\")\n",
    "HDweight = [HDweight[t] /sumWt for t in range(nHDs)]\n",
    "print(\"normalized weight is now\",np.sum(HDweight))\n",
    "HDvPop = inDF[\"HDvPop\"].to_list()\n",
    "hdCPx, hdCPy = inDF[\"centroid x\"], inDF[\"centroid y\"]\n",
    "hdCP = [Point(hdCPx[t], hdCPy[t]) for t in range(nHDs)]\n",
    "print(\"I read in\",nHDs,\"HD lists of units\") #vtds\")\n",
    "HDunitList = [inVTDlist[t].copy() for t in range(nHDs)]\n",
    "#HDunitList = [list() for t in range(nHDs)]\n",
    "#for t in range(nHDs):\n",
    "#    if t%500 == 0:\n",
    "#        print(\"working on converting HD\",t,\"from vtd list to unit list\")\n",
    "#    for v in inVTDlist[t]:  #this will skip over surrounded units, whose pops we have added to their surrounders\n",
    "#        if v in allUnits:\n",
    "#            HDunitList[t].append(allUnits.index(v))\n",
    "#    for c in unitCounties:\n",
    "#        if countyTractList[c][0] in inVTDlist[t]:\n",
    "#            u = allUnits.index(c+0.5)\n",
    "#            HDunitList[t].append(u)\n",
    "#    for j, L in enumerate(CCBlist):\n",
    "#        c = L[0]\n",
    "#        if countyTractList[c][0] in inVTDlist[t]:\n",
    "#            u = allUnits.index(j+0.25)\n",
    "#            HDunitList[t].append(u) \n",
    "            \n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse, bins=50, weights=unitPop,label=\"read-in\",histtype=\"step\")\n",
    "plt.legend()\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "print(\"orig unit avg and sd usage are\",r5(unpatchedAvg), r5(unpatchedSD) )\n",
    "plt.show()\n",
    "currAvg, currSD = unpatchedAvg, unpatchedSD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "id": "8014f0bf-74bb-40bc-b217-af4e204ea9a7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "upon restart, need to pull in unit topology and data\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the unpatched UNIT list file, e.g. ./state_map_files/MNunitTopologies_06Apr24.csv ./state_map_files/MNunitTopologies_06Apr24.csv\n"
     ]
    }
   ],
   "source": [
    "print(\"upon restart, need to pull in unit topology and data\")  #note, this won't have geometries for plotting, but fine for patching\n",
    "topologyFile = \"enter the unpatched UNIT list file, e.g. ./state_map_files/MNunitTopologies_06Apr24.csv\"\n",
    "infile = input(topologyFile)\n",
    "topDF = pd.read_csv(infile)\n",
    "unitCPx, unitCPy, unitPop = topDF[\"centroid x\"], topDF[\"centroid y\"], topDF[\"unitPop\"]\n",
    "nUnits = len(unitPop)\n",
    "unitCP = [Point(unitCPx[u], unitCPy[u]) for u in range(nUnits) ]\n",
    "onBorder = topDF[\"onBorder\"]\n",
    "borderSet = set()\n",
    "for i, onB in enumerate(onBorder):\n",
    "    if onB == 1:\n",
    "        borderSet.add(i)\n",
    "borderList = list(borderSet)\n",
    "\n",
    "nbrListString = topDF[\"neighborList\"]\n",
    "unitNbrs = [ast.literal_eval(nbrListString[u]) for u in range(nUnits)]\n",
    "unitParentVTDno = topDF[\"unitParentVTDno\"]  #NOTE: some units are VTD fragments, so they share a parentVTDno\n",
    "uVLstring = topDF[\"unitVTDlist\"]\n",
    "unitNbrs = [ast.literal_eval(uVLstring[u]) for u in range(nUnits)]\n",
    "allUnits = topDF[\"allUnits\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "5f3a5392-11f1-4061-a458-aecd834b2748",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working avg precinct-to-HDcP distance for HD 0\n",
      "working avg precinct-to-HDcP distance for HD 800\n",
      "working avg precinct-to-HDcP distance for HD 1600\n",
      "working avg precinct-to-HDcP distance for HD 2400\n",
      "working avg precinct-to-HDcP distance for HD 3200\n",
      "working avg precinct-to-HDcP distance for HD 4000\n",
      "working avg precinct-to-HDcP distance for HD 4800\n",
      "working avg precinct-to-HDcP distance for HD 5600\n",
      "all avgDist to HD centers computed\n"
     ]
    }
   ],
   "source": [
    "#needed for restart only  about 5sec per 2000 HDs\n",
    "avgDist = [0. for t in range(nHDs)]\n",
    "popHDlist = list()\n",
    "for t in range(nHDs):\n",
    "    if t%800 == 0:\n",
    "        print(\"working avg precinct-to-HDcP distance for HD\",t)\n",
    "    if HDvPop[t] > 0.1 * aDP:\n",
    "        avgDist[t] = np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]\n",
    "        popHDlist.append(t)\n",
    "print(\"all avgDist to HD centers computed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "ea0db02f-9df8-4906-acb4-086c29c0fcc1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking for discontiguities for HD 0\n",
      "checking for discontiguities for HD 500\n",
      "checking for discontiguities for HD 1000\n",
      "checking for discontiguities for HD 1500\n",
      "checking for discontiguities for HD 2000\n",
      "checking for discontiguities for HD 2500\n",
      "checking for discontiguities for HD 3000\n",
      "checking for discontiguities for HD 3500\n",
      "checking for discontiguities for HD 4000\n",
      "checking for discontiguities for HD 4500\n",
      "checking for discontiguities for HD 5000\n",
      "checking for discontiguities for HD 5500\n",
      "checking for discontiguities for HD 6000\n",
      "out of 6356 total HDs, there were 6356 0 0 0 HDs that were clean, discontig only, enclave-only, both problems.  Should all be zeroes\n"
     ]
    }
   ],
   "source": [
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()  #optional contiguity check\n",
    "for t in popHDlist:\n",
    "    if t%500 == 0:\n",
    "        print(\"checking for discontiguities for HD\",t)\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems.  Should all be zeroes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "27b42f93-dc87-4afe-8eb3-f30fdff4a737",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking unitUse, pop for county clusters\n",
      "6197 0.99557 95263.0\n",
      "6198 0.97617 64837.0\n"
     ]
    }
   ],
   "source": [
    "print(\"checking unitUse, pop for county clusters\")\n",
    "for uNo in allUnits:\n",
    "    if uNo - int(uNo) > 0.23 and uNo - int(uNo) < 0.27:\n",
    "        u = allUnits.index(uNo)\n",
    "        print(u,r5(unitUse[u]), unitPop[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "72941b8f-7be6-4a31-9377-618f44a34336",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "unpatchedUnitUse = unitUse.copy()              #... for safekeeping\n",
    "unpatchedHDlist =  [HDunitList[t].copy() for t in range(nHDs) ]\n",
    "unpatchedHDpop =   HDvPop.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "5f9ca091-1eb6-4135-a233-7f5ae0f5e3d1",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "unitUse = unpatchedUnitUse.copy()              #... for restarting\n",
    "HDunitList =  [unpatchedHDlist[t].copy() for t in range(nHDs) ]\n",
    "HDvPop =   unpatchedHDpop.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fc95ca58-c27f-4ac9-b6f7-234a94945f07",
   "metadata": {},
   "outputs": [],
   "source": [
    "#I believe BELOW UNDERUSED is faster now that we subbed wontEnclave for enclaveCheck"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "e9dd457d-fb37-49cf-9b19-19c17c328ede",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here, we exchange in under-used, THEN shed over-used\n",
      "Currently, we will stop patching when the overall sd of usage is less than 0.07\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated maxSD value 0.06\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we will stop patching on individual underused units when their usage exceeds 0.94\n",
      "this would currently cover a total of 1377 units\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated number of units to try boosting usage 150\n",
      "enter updated stopMinUse value for ending usage boost on a unit 0.97\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are currently 2402 units out of 6199 with usage below 0.97\n",
      "maxExchangePop is currently 0.05 fraction of avgDistrictPop\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter updated maxExchangePop fraction 0.05\n",
      "enter 1 to print out stats for every patched HD, otherwise enter reporting frequency 10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Let's further tighten the distro with exchanges up to 38704\n",
      "current avg and SD of unit usage are 1.00096 0.09746 . Now trying to increase up to 150 units' underusage\n",
      "all done trying to increase usage of unit 5234 final usage = 0.90571 235 sec elapsed 95 0 successful, failed patches, couldn't start= 50\n",
      "current avg and SD of usage are 1.00095 0.09608\n",
      "all done trying to increase usage of unit 733 final usage = 0.97199 439 sec elapsed 93 0 successful, failed patches, couldn't start= 49\n",
      "current avg and SD of usage are 1.00093 0.09459\n",
      "all done trying to increase usage of unit 4877 final usage = 0.84253 542 sec elapsed 56 0 successful, failed patches, couldn't start= 26\n",
      "current avg and SD of usage are 1.00093 0.09345\n",
      "all done trying to increase usage of unit 5210 final usage = 0.81267 646 sec elapsed 33 0 successful, failed patches, couldn't start= 34\n",
      "current avg and SD of usage are 1.00093 0.09302\n",
      "all done trying to increase usage of unit 5069 final usage = 0.83995 843 sec elapsed 46 0 successful, failed patches, couldn't start= 22\n",
      "current avg and SD of usage are 1.00092 0.09245\n",
      "all done trying to increase usage of unit 4692 final usage = 0.94884 1197 sec elapsed 111 0 successful, failed patches, couldn't start= 25\n",
      "current avg and SD of usage are 1.00092 0.0904\n",
      "all done trying to increase usage of unit 5027 final usage = 0.9161 1388 sec elapsed 68 0 successful, failed patches, couldn't start= 29\n",
      "current avg and SD of usage are 1.00091 0.08904\n",
      "all done trying to increase usage of unit 4681 final usage = 0.91981 1755 sec elapsed 85 0 successful, failed patches, couldn't start= 44\n",
      "current avg and SD of usage are 1.00091 0.08784\n",
      "all done trying to increase usage of unit 5155 final usage = 0.90887 2199 sec elapsed 86 0 successful, failed patches, couldn't start= 15\n",
      "current avg and SD of usage are 1.0009 0.0869\n",
      "begin usage increase for unit 909 with usage 0.77669 . Sec, total UU units tried = 2201 10\n",
      "all done trying to increase usage of unit 909 final usage = 0.96782 2343 sec elapsed 69 0 successful, failed patches, couldn't start= 40\n",
      "current avg and SD of usage are 1.00088 0.08556\n",
      "all done trying to increase usage of unit 5165 final usage = 0.97042 2837 sec elapsed 116 0 successful, failed patches, couldn't start= 50\n",
      "current avg and SD of usage are 1.00088 0.08414\n",
      "all done trying to increase usage of unit 4682 final usage = 0.96244 3558 sec elapsed 107 0 successful, failed patches, couldn't start= 20\n",
      "current avg and SD of usage are 1.00088 0.08292\n",
      "all done trying to increase usage of unit 5890 final usage = 0.9721 3799 sec elapsed 99 0 successful, failed patches, couldn't start= 79\n",
      "current avg and SD of usage are 1.00088 0.08088\n",
      "all done trying to increase usage of unit 5181 final usage = 0.92361 4187 sec elapsed 68 0 successful, failed patches, couldn't start= 41\n",
      "current avg and SD of usage are 1.00088 0.07997\n",
      "all done trying to increase usage of unit 5000 final usage = 0.90868 4570 sec elapsed 73 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00088 0.07931\n",
      "all done trying to increase usage of unit 1095 final usage = 0.94626 4759 sec elapsed 62 0 successful, failed patches, couldn't start= 7\n",
      "current avg and SD of usage are 1.00087 0.07846\n",
      "all done trying to increase usage of unit 6048 final usage = 0.9716 5024 sec elapsed 86 0 successful, failed patches, couldn't start= 32\n",
      "current avg and SD of usage are 1.00087 0.07734\n",
      "all done trying to increase usage of unit 1573 final usage = 0.8839 5323 sec elapsed 58 0 successful, failed patches, couldn't start= 57\n",
      "current avg and SD of usage are 1.00087 0.07658\n",
      "all done trying to increase usage of unit 1282 final usage = 0.97147 5436 sec elapsed 75 0 successful, failed patches, couldn't start= 23\n",
      "current avg and SD of usage are 1.00085 0.07518\n",
      "begin usage increase for unit 5213 with usage 0.79821 . Sec, total UU units tried = 5438 20\n",
      "all done trying to increase usage of unit 5213 final usage = 0.97157 5966 sec elapsed 89 0 successful, failed patches, couldn't start= 13\n",
      "current avg and SD of usage are 1.00085 0.07415\n",
      "all done trying to increase usage of unit 5150 final usage = 0.97128 6607 sec elapsed 91 0 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 1.00085 0.0733\n",
      "all done trying to increase usage of unit 1077 final usage = 0.97119 6748 sec elapsed 66 0 successful, failed patches, couldn't start= 17\n",
      "current avg and SD of usage are 1.00083 0.07213\n",
      "all done trying to increase usage of unit 1586 final usage = 0.94316 7229 sec elapsed 86 0 successful, failed patches, couldn't start= 38\n",
      "current avg and SD of usage are 1.00083 0.071\n",
      "all done trying to increase usage of unit 4743 final usage = 0.91992 7509 sec elapsed 67 0 successful, failed patches, couldn't start= 65\n",
      "current avg and SD of usage are 1.00083 0.07002\n",
      "all done trying to increase usage of unit 1571 final usage = 0.84036 7612 sec elapsed 23 0 successful, failed patches, couldn't start= 6\n",
      "current avg and SD of usage are 1.00083 0.06966\n",
      "all done trying to increase usage of unit 1563 final usage = 0.84589 7783 sec elapsed 23 0 successful, failed patches, couldn't start= 10\n",
      "current avg and SD of usage are 1.00083 0.06941\n",
      "all done trying to increase usage of unit 6082 final usage = 0.9708 8105 sec elapsed 78 0 successful, failed patches, couldn't start= 8\n",
      "current avg and SD of usage are 1.00083 0.06851\n",
      "all done trying to increase usage of unit 1533 final usage = 0.84974 8279 sec elapsed 22 0 successful, failed patches, couldn't start= 10\n",
      "current avg and SD of usage are 1.00083 0.06827\n",
      "all done trying to increase usage of unit 1568 final usage = 0.85295 8613 sec elapsed 27 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00083 0.06806\n",
      "begin usage increase for unit 5293 with usage 0.81259 . Sec, total UU units tried = 8615 30\n",
      "all done trying to increase usage of unit 5293 final usage = 0.85829 8729 sec elapsed 20 0 successful, failed patches, couldn't start= 20\n",
      "current avg and SD of usage are 1.00083 0.06785\n",
      "all done trying to increase usage of unit 5947 final usage = 0.89632 8874 sec elapsed 41 0 successful, failed patches, couldn't start= 94\n",
      "current avg and SD of usage are 1.00082 0.06736\n",
      "all done trying to increase usage of unit 1618 final usage = 0.92003 9156 sec elapsed 65 0 successful, failed patches, couldn't start= 40\n",
      "current avg and SD of usage are 1.00082 0.06665\n",
      "all done trying to increase usage of unit 1031 final usage = 0.97205 9415 sec elapsed 77 0 successful, failed patches, couldn't start= 22\n",
      "current avg and SD of usage are 1.00082 0.06575\n",
      "all done trying to increase usage of unit 1554 final usage = 0.97105 9829 sec elapsed 92 0 successful, failed patches, couldn't start= 3\n",
      "current avg and SD of usage are 1.00082 0.06455\n",
      "all done trying to increase usage of unit 903 final usage = 0.97025 10088 sec elapsed 62 0 successful, failed patches, couldn't start= 19\n",
      "current avg and SD of usage are 1.00081 0.06381\n",
      "all done trying to increase usage of unit 1712 final usage = 0.97057 10414 sec elapsed 86 0 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 1.00082 0.06264\n",
      "all done trying to increase usage of unit 1584 final usage = 0.85197 10614 sec elapsed 16 0 successful, failed patches, couldn't start= 22\n",
      "current avg and SD of usage are 1.00082 0.06245\n",
      "all done trying to increase usage of unit 4674 final usage = 0.97081 11184 sec elapsed 79 0 successful, failed patches, couldn't start= 24\n",
      "current avg and SD of usage are 1.00081 0.06142\n",
      "all done trying to increase usage of unit 1033 final usage = 0.97087 11395 sec elapsed 59 0 successful, failed patches, couldn't start= 7\n",
      "current avg and SD of usage are 1.00081 0.06075\n",
      "begin usage increase for unit 5169 with usage 0.82441 . Sec, total UU units tried = 11397 40\n",
      "all done trying to increase usage of unit 5169 final usage = 0.97133 11948 sec elapsed 84 0 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 1.00081 0.06004\n",
      "all done trying to increase usage of unit 5160 final usage = 0.9706 12600 sec elapsed 71 0 successful, failed patches, couldn't start= 19\n",
      "current avg and SD of usage are 1.00081 0.05945\n"
     ]
    }
   ],
   "source": [
    "#FIRST PATCHING BLOCK - boosting underuse.  Suppresses long strings.  For some states (e.g. MA), do overused first. MA:over-und-over-und\n",
    "print(\"Here, we exchange in under-used, THEN shed over-used\")\n",
    "maxSD = 0.07  #0.07  #0.05   #adjust down if distro already tight\n",
    "print(\"Currently, we will stop patching when the overall sd of usage is less than\",maxSD)\n",
    "maxSD = float(input(\"enter updated maxSD value\"))\n",
    "#stopMinUse = 1. - maxSD\n",
    "#print(\"we will stop patching on individual underused units when their usage exceeds\",r5(stopMinUse))\n",
    "maxNtries = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < stopMinUse:\n",
    "        maxNtries +=1\n",
    "print(\"this would currently cover a total of\",maxNtries,\"units\")\n",
    "maxNtries = int(input(\"enter updated number of units to try boosting usage\"))\n",
    "stopMinUse = float(input(\"enter updated stopMinUse value for ending usage boost on a unit; I reco 0.97\"))\n",
    "nInPlay = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < stopMinUse:\n",
    "        nInPlay +=1\n",
    "print(\"there are currently\",nInPlay,\"units out of\",nUnits,\"with usage below\",stopMinUse)\n",
    "nSmallUsers = 5\n",
    "maxExchangePop = 0.05*aDP \n",
    "print(\"maxExchangePop is currently\",r5(maxExchangePop/aDP),\"fraction of avgDistrictPop\")\n",
    "newMEPratio = float(input(\"Enter updated maxExchangePop fraction\"))\n",
    "maxExchangePop = newMEPratio*aDP\n",
    "debug1 = int(input(\"enter 1 to print out stats for every patched HD, otherwise enter reporting frequency\"))\n",
    "print(\"Let's further tighten the distro with exchanges up to\",int(maxExchangePop)) #1/25/24\n",
    "maxGap = 0.9 * np.median(unitPop) \n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "\n",
    "attemptedSmallUs, startTime = list(), time.time()\n",
    "print(\"current avg and SD of unit usage are\",r5(currAvg), r5(currSD),\". Now trying to increase up to\",maxNtries,\"units' underusage\" )\n",
    "startTime = time.time()\n",
    "while currSD > maxSD and len(attemptedSmallUs) < maxNtries: \n",
    "    #each round, find the (5) most underused not-yet-tried units. Pick the unit w/ most overuse of it + 1-nbrs\n",
    "    idx = np.argsort(unitUse)\n",
    "    idxNo, nSmallFound, smallUsers = 0,0,list()\n",
    "    while nSmallFound < nSmallUsers:\n",
    "        consideredSmallU = idx[idxNo]\n",
    "        if consideredSmallU not in attemptedSmallUs:\n",
    "            smallUsers.append(consideredSmallU)\n",
    "            nSmallFound +=1\n",
    "        idxNo +=1\n",
    "    UUUclusters = [ [b] + unitNbrs[b] for b in smallUsers ]\n",
    "    smallUnderUse = [np.sum([(unitUse[j] - 1.) for j in UUUclusters[i] ]) for i in range(nSmallUsers) ]\n",
    "    smallI = smallUnderUse.index(np.max(smallUnderUse))\n",
    "    UUU = smallUsers[ smallI ]  #pick the unit that centers cluster with least composite use\n",
    "    attemptedSmallUs.append(UUU)  #so we don't try this unit again in a future loop\n",
    "    UUUc = UUUclusters[smallI]  #the list of this unit and ALL its neighbors (to be curated below ...)\n",
    "    if len(attemptedSmallUs) % debug1 == 0:\n",
    "        print(\"begin usage increase for unit\",UUU,\"with usage\",r5(unitUse[UUU]),\". Sec, total UU units tried =\",\n",
    "              int(time.time()-startTime),len(attemptedSmallUs) )\n",
    "    for u in UUUc.copy():\n",
    "        if unitUse[u] > 1.:\n",
    "            UUUc.remove(u)  #...drop any overused neighbors of the primary UUU from the target sheddable cluster\n",
    "    uuuHDs, uuuDists = list(), list()\n",
    "    for t in popHDlist:  #finding all HDs with at least one cluster member on the boundary\n",
    "        if UUU not in HDunitList[t]:\n",
    "            HDadjoinSet = set( getAdjoiners(HDunitList[t],unitNbrs) )\n",
    "            if len(HDadjoinSet.intersection(UUUc) ) > 0: #the UUU or one of its underused 1-neighbors adjoins this HD\n",
    "                uuuHDs.append(t)  #Note: we'll check later if we can contiguously pick up the UUU's cluster\n",
    "                uuuDists.append( unitCP[UUU].distance(hdCP[t]) / avgDist[t] )\n",
    "    idx0 = np.argsort(uuuDists)\n",
    "    nPatchSuccess, nPatchFail, nCouldntStart, idxNo = 0,0,0,-1\n",
    "    while unitUse[UUU] < stopMinUse and idxNo < 0.8*len(uuuHDs): #arbitrarily only examine 80% closest of HDs\n",
    "        excess, giveUpOnShedding = 99*aDP, True  #default = failed swap\n",
    "        idxNo += 1\n",
    "        if idxNo % 20 == 0 and debug1 == 1:\n",
    "            print(\"try to add unit\",UUU,\"from\",abs(idxNo),\"th HD.  Usage up to\",unitUse[UUU] )\n",
    "        t = uuuHDs[idx0[idxNo]]\n",
    "        trySet = set(HDunitList[t]).union(set(UUUc))\n",
    "        contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        loopUUUc = UUUc.copy()  #default; we will add whole cluster\n",
    "        if not (contig and complementContig): #we can't add whole cluster; neighbors may be enclavy.   Try just adding the UUU\n",
    "            trySet = set(HDunitList[t]).union({UUU})\n",
    "            contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "            loopUUUc = [UUU]\n",
    "        if contig and complementContig:  #we can at least add the cluster, let's go for more\n",
    "            HDuuuSet = set(loopUUUc).difference(set(HDunitList[t]))  #the subset of the UUU cluster that adjoins (NOT in) this HD\n",
    "            HDuuuCpop = np.sum([unitPop[u] for u in HDuuuSet])\n",
    "            giveUpOnAdding = False            \n",
    "            addCandidates, addUseDists = list(), list()\n",
    "            uuCandidates = getAdjoiners(trySet, unitNbrs)  #any adjoiner can be picked up, even if far from UUUc\n",
    "            for u in uuCandidates:\n",
    "                if HDuuuCpop + unitPop[u] <= maxExchangePop:\n",
    "                    addCandidates.append(u)  #Below's relative scoring of use and distance is a bit arbitrary\n",
    "                    addUseDists.append((unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t])  #bias toward close, underused\n",
    "            if len(addCandidates) == 0:\n",
    "                giveUpOnAdding = True\n",
    "            while HDuuuCpop < maxExchangePop and not giveUpOnAdding:\n",
    "                addNneighbors = [len( set(unitNbrs[addC]).intersection(trySet) ) for addC in addCandidates ]\n",
    "                addScores = addUseDists.copy()\n",
    "                for jjj, u in enumerate(addCandidates):\n",
    "                    if addNneighbors[jjj] == 1:\n",
    "                        addScores[jjj] += 0.4321    #discourage growing fingers\n",
    "                #print(\"HDuuuCpop is now\",HDuuuCpop)\n",
    "                idx, ij, notYetPicked = np.argsort(addScores), 0, True\n",
    "                while ij < 0.5*len(addScores) and notYetPicked:\n",
    "                    listNo = idx[ij]   #work from low to high score\n",
    "                    addU = addCandidates[listNo]\n",
    "                    cContig = wontEnclave(addU, list(trySet), unitNbrs, borderUnits)  #4/20/24 sub this in as faster? vs below line\n",
    "                    #contig,cContig, __, ___ = enclaveCheck(list(trySet.union({addU}) ), unitNbrs)  #4/20/24 this is unnec slow\n",
    "                    if cContig: #contig and cContig:\n",
    "                        notYetPicked = False\n",
    "                        HDuuuCpop += unitPop[addU]\n",
    "                        HDuuuSet.add(addU)\n",
    "                        trySet.add(addU)\n",
    "                        del addUseDists[addCandidates.index(addU)]\n",
    "                        del addCandidates[addCandidates.index(addU)]                        \n",
    "                        for uu in list(set(unitNbrs[addU]).difference(trySet) ): \n",
    "                            if uu not in addCandidates and unitPop[uu] + HDuuuCpop < maxExchangePop and unitUse[uu] < 1.01:\n",
    "                                addCandidates.append(uu)\n",
    "                                addUseDists.append( (unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t] )\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnAdding = True  #all candidates would create a discontig, so can't shed any more units\n",
    "            addSet = HDuuuSet.copy()  #we're done building the list of underused units to add to this HD\n",
    "            trySet = set(HDunitList[t]).union(addSet) \n",
    "            excess = np.sum([unitPop[u] for u in trySet]) - aDP\n",
    "            shedCandidates, shedScores, giveUpOnShedding = list(), list(), False\n",
    "            bdryCandidates = getBdryNonEdgers(trySet, unitNbrs)  #new - any boundary unit can be shed, even if far from OUUc\n",
    "            for u in bdryCandidates:\n",
    "                if unitPop[u] <= excess + maxGap:\n",
    "                    shedCandidates.append(u)\n",
    "                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])  #bias toward OVERUSED, far\n",
    "            if len(shedCandidates) == 0:\n",
    "                giveUpOnShedding = True\n",
    "            shedSet = set()\n",
    "            while excess > maxGap and not giveUpOnShedding:\n",
    "                #print(\"excess pop is now\",excess,\"for HD\",t)\n",
    "                idx, ij, notYetPicked = np.argsort(shedScores), 0, True\n",
    "                while ij < len(shedScores) and notYetPicked:\n",
    "                    listNo = idx[-1-ij]   #work from high to low score\n",
    "                    shedU = shedCandidates[listNo]\n",
    "                    if shedScores[listNo] <= 0:  #we're delving into the underused; stop adding to shed list\n",
    "                        break\n",
    "                    if excess - unitPop[shedU] >= -1*maxGap:\n",
    "                        contig,cContig, __, ___ = enclaveCheck(list(trySet.difference({shedU}) ), unitNbrs)\n",
    "                        if contig and cContig:\n",
    "                            notYetPicked = False\n",
    "                            excess -= unitPop[shedU]\n",
    "                            trySet.remove(shedU)\n",
    "                            shedSet.add(shedU)\n",
    "                            del shedScores[shedCandidates.index(shedU)]\n",
    "                            del shedCandidates[shedCandidates.index(shedU)]\n",
    "                            newSheddables = set(unitNbrs[shedU]).intersection(trySet)\n",
    "                            for u in newSheddables:\n",
    "                                if excess - unitPop[u] >= -1*maxGap and u not in shedCandidates:\n",
    "                                    shedCandidates.append(u)  #we'll check enclavity if ever picked\n",
    "                                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])\n",
    "                            for kkk, u in enumerate(shedCandidates): #checking if this shed eliminates high-pop future sheds ...\n",
    "                                if excess - unitPop[u] < -1*maxGap:\n",
    "                                    del shedScores[kkk]\n",
    "                                    del shedCandidates[kkk]\n",
    "                    ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnShedding = True  #all shedcandidates would create a discontig, so can't shed enough units to square pop\n",
    "            legitSwap = False\n",
    "            if abs(excess) <= 2.*maxGap:  #giving ourselves a bit more margin after exchanges\n",
    "                contig,cContig, __, ___ = enclaveCheck(list(trySet), unitNbrs) \n",
    "                if contig and cContig:\n",
    "                    legitSwap = True\n",
    "            if legitSwap:\n",
    "                for u in shedSet:\n",
    "                    unitUse[u] -= HDweight[t] * nDistricts\n",
    "                for u in addSet:\n",
    "                    unitUse[u] += HDweight[t] * nDistricts\n",
    "                HDunitList[t] = list(trySet)\n",
    "                HDvPop[t] = np.sum([ unitPop[u] for u in HDunitList[t] ])\n",
    "                nPatchSuccess +=1\n",
    "                #print(\"we added\",addSet,\"and shed units\",shedSet,\"from HD\",t)\n",
    "            else:\n",
    "                nPatchFail +=1\n",
    "        else:  #adding neither the UUU cluster or just the UUU worked; couldn't even start\n",
    "            nCouldntStart +=1\n",
    "            # end of shed + add patching on this HD\n",
    "            #print(\"shed and patched for HD, OUU\",t,OUU)\n",
    "\n",
    "    print(\"all done trying to increase usage of unit\",UUU,\"final usage =\",r5(unitUse[UUU]),int(time.time()-startTime),\"sec elapsed\",\n",
    "         nPatchSuccess,nPatchFail,\"successful, failed patches, couldn't start=\",nCouldntStart)\n",
    "    currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "    print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e2377b41-61df-4f0d-9d87-a0557362328d",
   "metadata": {},
   "outputs": [],
   "source": [
    ".99959 0.09151  8:44 0.08996"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "861f29d3-b727-49af-90a8-aa9a963e0741",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unpatched, patched use avgs are 1.00096 1.00081 and their SDs are 0.09746 0.05945\n",
      "And here is the pop distro\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 0 out of 6361\n",
      "working on HD 300 out of 6361\n",
      "working on HD 600 out of 6361\n",
      "working on HD 900 out of 6361\n",
      "working on HD 1200 out of 6361\n",
      "working on HD 1500 out of 6361\n",
      "working on HD 1800 out of 6361\n",
      "working on HD 2100 out of 6361\n",
      "working on HD 2400 out of 6361\n",
      "working on HD 2700 out of 6361\n",
      "working on HD 3000 out of 6361\n",
      "working on HD 3300 out of 6361\n",
      "working on HD 3600 out of 6361\n",
      "working on HD 3900 out of 6361\n",
      "working on HD 4200 out of 6361\n",
      "working on HD 4500 out of 6361\n",
      "working on HD 4800 out of 6361\n",
      "working on HD 5100 out of 6361\n",
      "working on HD 5400 out of 6361\n",
      "working on HD 5700 out of 6361\n",
      "working on HD 6000 out of 6361\n",
      "working on HD 6300 out of 6361\n",
      "all done checking HD and complement contiguity for all 6361 HDs\n"
     ]
    }
   ],
   "source": [
    "patchedUse, unpUse = [0.]*nUnits, [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        patchedUse[u] += HDweight[t] * nDistricts\n",
    "    for u in unpatchedHDlist[t]:\n",
    "        unpUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(patchedUse,bins=50, label=\"patched\",histtype=\"step\")\n",
    "plt.hist(unpUse, bins=50, label=\"unpatched\",histtype=\"step\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "patchedAvg, patchedSD = getWeightedAvgAndSD(patchedUse,unitPop)\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unpUse,unitPop)\n",
    "print(\"unpatched, patched use avgs are\",r5(unpatchedAvg), r5(patchedAvg),\"and their SDs are\",r5(unpatchedSD), r5(patchedSD) )\n",
    "print(\"And here is the pop distro\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP, ls=\"--\",color=\"orange\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "for t in popHDlist:\n",
    "    if t%300 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs)  #these HDunitLists now appear to be sets\n",
    "    if not unbroken or not noEnclave:\n",
    "        print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "1ee72cf0-618e-411f-aa37-518ac2c679ce",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lets write these UNIT lists to a file\n"
     ]
    }
   ],
   "source": [
    "#optional intermediate save\n",
    "print(\"Lets write these UNIT lists to a file\")\n",
    "HDvPop = [0. for t in range(nHDs)]  #writing UNIT lists to a file\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"underPatched.csv\" #\"contigUnpatchedB.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "77c07848-50c2-4fe9-8841-768b02bf4ac4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "default use threshold for moving on to next overused unit is 1.08\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated stopMaxUse value 1.03\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are currently 1914 units out of 6199 with usage above 1.03\n",
      "maxExchangePop is currently 0.05 fraction of avgDistrictPop\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter updated maxExchangePop fraction 0.03\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this block reduces overuse, with exchanges up to 23222\n",
      "current avg and SD of unit usage are 1.00081 0.05945 . Now trying to reduce up to 1914 units' overusage\n",
      "starting to reduce usage for unit 3512 with usage 1.18922 . Total units tried = 1\n",
      "try to drop unit 3512 from 38 th HD.  usage down to 1.1149271923310258\n",
      "try to drop unit 3512 from 76 th HD.  usage down to 1.050485768426562\n",
      "all done trying to reduce usage of unit 3512 final usage = 1.02898 18 sec elapsed 67 0 successful, failed patches, couldn't start= 19\n",
      "current avg and SD of usage are 1.00078 0.05849\n",
      "starting to reduce usage for unit 1209 with usage 1.1358 . Total units tried = 2\n",
      "try to drop unit 1209 from 26 th HD.  usage down to 1.0940108261454258\n",
      "try to drop unit 1209 from 52 th HD.  usage down to 1.047648862729369\n",
      "all done trying to reduce usage of unit 1209 final usage = 1.02982 26 sec elapsed 50 0 successful, failed patches, couldn't start= 10\n",
      "current avg and SD of usage are 1.00077 0.05796\n",
      "starting to reduce usage for unit 3513 with usage 1.12979 . Total units tried = 3\n",
      "try to drop unit 3513 from 37 th HD.  usage down to 1.086939231524934\n",
      "try to drop unit 3513 from 74 th HD.  usage down to 1.056381778263581\n",
      "all done trying to reduce usage of unit 3513 final usage = 1.02967 50 sec elapsed 51 0 successful, failed patches, couldn't start= 56\n",
      "current avg and SD of usage are 1.00075 0.05746\n",
      "starting to reduce usage for unit 5950 with usage 1.12909 . Total units tried = 4\n",
      "try to drop unit 5950 from 29 th HD.  usage down to 1.0979651833126607\n",
      "all done trying to reduce usage of unit 5950 final usage = 1.02859 186 sec elapsed 45 0 successful, failed patches, couldn't start= 11\n",
      "current avg and SD of usage are 1.00076 0.05678\n",
      "starting to reduce usage for unit 1889 with usage 1.11906 . Total units tried = 5\n",
      "try to drop unit 1889 from 52 th HD.  usage down to 1.092632420690612\n",
      "try to drop unit 1889 from 104 th HD.  usage down to 1.0794632874130998\n",
      "try to drop unit 1889 from 156 th HD.  usage down to 1.0606177590383374\n",
      "try to drop unit 1889 from 208 th HD.  usage down to 1.0390360893763655\n",
      "all done trying to reduce usage of unit 1889 final usage = 1.02841 274 sec elapsed 50 0 successful, failed patches, couldn't start= 167\n",
      "current avg and SD of usage are 1.00076 0.05621\n",
      "starting to reduce usage for unit 2304 with usage 1.12135 . Total units tried = 6\n",
      "try to drop unit 2304 from 37 th HD.  usage down to 1.0547010795786647\n",
      "all done trying to reduce usage of unit 2304 final usage = 1.02966 297 sec elapsed 49 0 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 1.00074 0.05573\n",
      "starting to reduce usage for unit 3762 with usage 1.11621 . Total units tried = 7\n",
      "try to drop unit 3762 from 33 th HD.  usage down to 1.0485544505680353\n",
      "all done trying to reduce usage of unit 3762 final usage = 1.02926 310 sec elapsed 37 0 successful, failed patches, couldn't start= 13\n",
      "current avg and SD of usage are 1.00073 0.05538\n",
      "starting to reduce usage for unit 4732 with usage 1.10729 . Total units tried = 8\n",
      "try to drop unit 4732 from 30 th HD.  usage down to 1.0582174991177618\n",
      "all done trying to reduce usage of unit 4732 final usage = 1.02886 351 sec elapsed 46 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00074 0.05492\n",
      "starting to reduce usage for unit 4603 with usage 1.1041 . Total units tried = 9\n",
      "try to drop unit 4603 from 21 th HD.  usage down to 1.060191448072825\n",
      "all done trying to reduce usage of unit 4603 final usage = 1.02831 379 sec elapsed 35 1 successful, failed patches, couldn't start= 3\n",
      "current avg and SD of usage are 1.00073 0.05434\n",
      "starting to reduce usage for unit 3687 with usage 1.10436 . Total units tried = 10\n",
      "try to drop unit 3687 from 20 th HD.  usage down to 1.0746588920177762\n",
      "try to drop unit 3687 from 40 th HD.  usage down to 1.044049764700008\n",
      "all done trying to reduce usage of unit 3687 final usage = 1.02761 392 sec elapsed 37 0 successful, failed patches, couldn't start= 9\n",
      "current avg and SD of usage are 1.00072 0.054\n",
      "starting to reduce usage for unit 5134 with usage 1.10141 . Total units tried = 11\n",
      "all done trying to reduce usage of unit 5134 final usage = 1.02593 400 sec elapsed 20 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00069 0.05349\n",
      "starting to reduce usage for unit 2666 with usage 1.10027 . Total units tried = 12\n",
      "try to drop unit 2666 from 33 th HD.  usage down to 1.0488502845409946\n",
      "all done trying to reduce usage of unit 2666 final usage = 1.02963 425 sec elapsed 42 0 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 1.00068 0.05318\n",
      "starting to reduce usage for unit 2367 with usage 1.09688 . Total units tried = 13\n",
      "try to drop unit 2367 from 45 th HD.  usage down to 1.0350184314899822\n",
      "all done trying to reduce usage of unit 2367 final usage = 1.02826 443 sec elapsed 43 0 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 1.00067 0.05283\n",
      "starting to reduce usage for unit 5794 with usage 1.09731 . Total units tried = 14\n",
      "try to drop unit 5794 from 28 th HD.  usage down to 1.049454871001116\n",
      "all done trying to reduce usage of unit 5794 final usage = 1.0299 580 sec elapsed 25 0 successful, failed patches, couldn't start= 13\n",
      "current avg and SD of usage are 1.00067 0.05247\n",
      "starting to reduce usage for unit 2962 with usage 1.09358 . Total units tried = 15\n",
      "try to drop unit 2962 from 27 th HD.  usage down to 1.0372119951848222\n",
      "all done trying to reduce usage of unit 2962 final usage = 1.02982 599 sec elapsed 26 0 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 1.00066 0.05213\n",
      "starting to reduce usage for unit 5916 with usage 1.09548 . Total units tried = 16\n",
      "try to drop unit 5916 from 15 th HD.  usage down to 1.0787631039485872\n",
      "try to drop unit 5916 from 30 th HD.  usage down to 1.0596191578980256\n",
      "try to drop unit 5916 from 45 th HD.  usage down to 1.034167101410529\n",
      "all done trying to reduce usage of unit 5916 final usage = 1.0292 658 sec elapsed 37 1 successful, failed patches, couldn't start= 10\n",
      "current avg and SD of usage are 1.00066 0.05173\n",
      "starting to reduce usage for unit 2460 with usage 1.09187 . Total units tried = 17\n",
      "all done trying to reduce usage of unit 2460 final usage = 1.02931 675 sec elapsed 32 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00065 0.05147\n",
      "starting to reduce usage for unit 6143 with usage 1.08893 . Total units tried = 18\n",
      "try to drop unit 6143 from 33 th HD.  usage down to 1.0678430839766182\n",
      "try to drop unit 6143 from 66 th HD.  usage down to 1.0339177740883763\n",
      "all done trying to reduce usage of unit 6143 final usage = 1.02842 704 sec elapsed 34 0 successful, failed patches, couldn't start= 34\n",
      "current avg and SD of usage are 1.00064 0.05105\n",
      "starting to reduce usage for unit 4731 with usage 1.08855 . Total units tried = 19\n",
      "try to drop unit 4731 from 27 th HD.  usage down to 1.0599653740760098\n",
      "try to drop unit 4731 from 54 th HD.  usage down to 1.0312087616807388\n",
      "all done trying to reduce usage of unit 4731 final usage = 1.02912 785 sec elapsed 37 3 successful, failed patches, couldn't start= 17\n",
      "current avg and SD of usage are 1.00063 0.05074\n",
      "starting to reduce usage for unit 2428 with usage 1.0881 . Total units tried = 20\n",
      "try to drop unit 2428 from 22 th HD.  usage down to 1.0594563846202996\n",
      "all done trying to reduce usage of unit 2428 final usage = 1.02831 812 sec elapsed 29 0 successful, failed patches, couldn't start= 14\n",
      "current avg and SD of usage are 1.00062 0.05049\n",
      "starting to reduce usage for unit 3434 with usage 1.0879 . Total units tried = 21\n",
      "try to drop unit 3434 from 17 th HD.  usage down to 1.0619264045169945\n",
      "all done trying to reduce usage of unit 3434 final usage = 1.0299 824 sec elapsed 27 0 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 1.00061 0.05024\n",
      "starting to reduce usage for unit 5861 with usage 1.08515 . Total units tried = 22\n",
      "try to drop unit 5861 from 31 th HD.  usage down to 1.0639171475404212\n",
      "all done trying to reduce usage of unit 5861 final usage = 1.02955 898 sec elapsed 43 1 successful, failed patches, couldn't start= 12\n",
      "current avg and SD of usage are 1.00061 0.04991\n",
      "starting to reduce usage for unit 203 with usage 1.08476 . Total units tried = 23\n",
      "try to drop unit 203 from 41 th HD.  usage down to 1.0313508653358787\n",
      "all done trying to reduce usage of unit 203 final usage = 1.02842 925 sec elapsed 33 0 successful, failed patches, couldn't start= 8\n",
      "current avg and SD of usage are 1.00061 0.04967\n",
      "starting to reduce usage for unit 2529 with usage 1.08445 . Total units tried = 24\n",
      "all done trying to reduce usage of unit 2529 final usage = 1.02917 936 sec elapsed 27 0 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 1.0006 0.04943\n",
      "starting to reduce usage for unit 4794 with usage 1.08433 . Total units tried = 25\n",
      "try to drop unit 4794 from 27 th HD.  usage down to 1.0586179730549818\n",
      "try to drop unit 4794 from 54 th HD.  usage down to 1.039324172240813\n",
      "all done trying to reduce usage of unit 4794 final usage = 1.02929 970 sec elapsed 34 10 successful, failed patches, couldn't start= 14\n",
      "current avg and SD of usage are 1.0006 0.0491\n",
      "starting to reduce usage for unit 1228 with usage 1.08414 . Total units tried = 26\n",
      "try to drop unit 1228 from 19 th HD.  usage down to 1.052457133678832\n",
      "all done trying to reduce usage of unit 1228 final usage = 1.02815 977 sec elapsed 27 0 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 1.00059 0.04884\n",
      "starting to reduce usage for unit 4255 with usage 1.08072 . Total units tried = 27\n",
      "try to drop unit 4255 from 32 th HD.  usage down to 1.0353129736115994\n",
      "all done trying to reduce usage of unit 4255 final usage = 1.02855 990 sec elapsed 32 0 successful, failed patches, couldn't start= 3\n",
      "current avg and SD of usage are 1.00058 0.04855\n",
      "starting to reduce usage for unit 2299 with usage 1.08025 . Total units tried = 28\n",
      "try to drop unit 2299 from 20 th HD.  usage down to 1.0511278185775317\n",
      "all done trying to reduce usage of unit 2299 final usage = 1.02996 1008 sec elapsed 30 0 successful, failed patches, couldn't start= 7\n",
      "current avg and SD of usage are 1.00058 0.04834\n",
      "starting to reduce usage for unit 5793 with usage 1.08262 . Total units tried = 29\n",
      "try to drop unit 5793 from 22 th HD.  usage down to 1.0378992601351875\n",
      "all done trying to reduce usage of unit 5793 final usage = 1.02926 1073 sec elapsed 22 0 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 1.00058 0.04811\n",
      "starting to reduce usage for unit 2036 with usage 1.07951 . Total units tried = 30\n",
      "try to drop unit 2036 from 36 th HD.  usage down to 1.047717330854189\n",
      "all done trying to reduce usage of unit 2036 final usage = 1.02848 1094 sec elapsed 26 0 successful, failed patches, couldn't start= 22\n",
      "current avg and SD of usage are 1.00057 0.04785\n",
      "starting to reduce usage for unit 3351 with usage 1.07757 . Total units tried = 31\n",
      "try to drop unit 3351 from 21 th HD.  usage down to 1.0427566214382025\n",
      "all done trying to reduce usage of unit 3351 final usage = 1.02924 1101 sec elapsed 23 0 successful, failed patches, couldn't start= 3\n",
      "current avg and SD of usage are 1.00057 0.04761\n",
      "starting to reduce usage for unit 5946 with usage 1.07712 . Total units tried = 32\n",
      "try to drop unit 5946 from 18 th HD.  usage down to 1.0613076076914054\n",
      "try to drop unit 5946 from 36 th HD.  usage down to 1.0426274362971724\n",
      "all done trying to reduce usage of unit 5946 final usage = 1.02809 1137 sec elapsed 30 4 successful, failed patches, couldn't start= 10\n",
      "current avg and SD of usage are 1.00057 0.04731\n",
      "starting to reduce usage for unit 3793 with usage 1.07703 . Total units tried = 33\n",
      "try to drop unit 3793 from 30 th HD.  usage down to 1.034544322022359\n",
      "all done trying to reduce usage of unit 3793 final usage = 1.02983 1149 sec elapsed 25 0 successful, failed patches, couldn't start= 6\n",
      "current avg and SD of usage are 1.00056 0.04714\n",
      "starting to reduce usage for unit 232 with usage 1.07628 . Total units tried = 34\n",
      "all done trying to reduce usage of unit 232 final usage = 1.0289 1173 sec elapsed 26 0 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 1.00056 0.04696\n",
      "starting to reduce usage for unit 3363 with usage 1.075 . Total units tried = 35\n",
      "all done trying to reduce usage of unit 3363 final usage = 1.02784 1182 sec elapsed 18 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00055 0.04675\n",
      "starting to reduce usage for unit 228 with usage 1.07316 . Total units tried = 36\n",
      "all done trying to reduce usage of unit 228 final usage = 1.02907 1193 sec elapsed 21 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00054 0.04661\n",
      "starting to reduce usage for unit 4604 with usage 1.07224 . Total units tried = 37\n",
      "try to drop unit 4604 from 29 th HD.  usage down to 1.0358568430553223\n",
      "all done trying to reduce usage of unit 4604 final usage = 1.02827 1205 sec elapsed 27 2 successful, failed patches, couldn't start= 6\n",
      "current avg and SD of usage are 1.00054 0.04637\n",
      "starting to reduce usage for unit 2502 with usage 1.07363 . Total units tried = 38\n",
      "all done trying to reduce usage of unit 2502 final usage = 1.02834 1218 sec elapsed 27 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00053 0.0462\n",
      "starting to reduce usage for unit 2344 with usage 1.07064 . Total units tried = 39\n",
      "try to drop unit 2344 from 28 th HD.  usage down to 1.0325135316052168\n",
      "all done trying to reduce usage of unit 2344 final usage = 1.02935 1236 sec elapsed 26 0 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 1.00053 0.04605\n",
      "starting to reduce usage for unit 3221 with usage 1.07033 . Total units tried = 40\n",
      "try to drop unit 3221 from 24 th HD.  usage down to 1.0318908592254212\n",
      "all done trying to reduce usage of unit 3221 final usage = 1.02976 1245 sec elapsed 16 1 successful, failed patches, couldn't start= 8\n",
      "current avg and SD of usage are 1.00053 0.04591\n",
      "starting to reduce usage for unit 5693 with usage 1.07003 . Total units tried = 41\n",
      "all done trying to reduce usage of unit 5693 final usage = 1.02938 1253 sec elapsed 9 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00052 0.04568\n",
      "starting to reduce usage for unit 2925 with usage 1.06953 . Total units tried = 42\n",
      "try to drop unit 2925 from 19 th HD.  usage down to 1.0312203883434292\n",
      "all done trying to reduce usage of unit 2925 final usage = 1.02906 1278 sec elapsed 18 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00052 0.04547\n",
      "starting to reduce usage for unit 2400 with usage 1.06696 . Total units tried = 43\n",
      "try to drop unit 2400 from 27 th HD.  usage down to 1.0301881990665156\n",
      "all done trying to reduce usage of unit 2400 final usage = 1.02848 1291 sec elapsed 23 0 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 1.00051 0.04534\n",
      "starting to reduce usage for unit 4735 with usage 1.06695 . Total units tried = 44\n",
      "try to drop unit 4735 from 21 th HD.  usage down to 1.050821649793283\n",
      "try to drop unit 4735 from 42 th HD.  usage down to 1.0382687296385276\n",
      "all done trying to reduce usage of unit 4735 final usage = 1.02785 1327 sec elapsed 24 11 successful, failed patches, couldn't start= 13\n",
      "current avg and SD of usage are 1.00051 0.04514\n",
      "starting to reduce usage for unit 3215 with usage 1.06986 . Total units tried = 45\n",
      "try to drop unit 3215 from 25 th HD.  usage down to 1.045879026297118\n",
      "all done trying to reduce usage of unit 3215 final usage = 1.0272 1338 sec elapsed 20 1 successful, failed patches, couldn't start= 16\n",
      "current avg and SD of usage are 1.00051 0.04499\n",
      "starting to reduce usage for unit 6050 with usage 1.06497 . Total units tried = 46\n",
      "all done trying to reduce usage of unit 6050 final usage = 1.02861 1355 sec elapsed 20 0 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 1.0005 0.04486\n",
      "starting to reduce usage for unit 2623 with usage 1.06364 . Total units tried = 47\n",
      "try to drop unit 2623 from 27 th HD.  usage down to 1.0363619569567821\n",
      "all done trying to reduce usage of unit 2623 final usage = 1.02953 1367 sec elapsed 22 0 successful, failed patches, couldn't start= 9\n",
      "current avg and SD of usage are 1.0005 0.04473\n",
      "starting to reduce usage for unit 2774 with usage 1.0652 . Total units tried = 48\n",
      "try to drop unit 2774 from 14 th HD.  usage down to 1.0361113377831819\n",
      "all done trying to reduce usage of unit 2774 final usage = 1.0289 1372 sec elapsed 16 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00049 0.04458\n",
      "starting to reduce usage for unit 1760 with usage 1.064 . Total units tried = 49\n",
      "all done trying to reduce usage of unit 1760 final usage = 1.02881 1389 sec elapsed 20 0 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 1.00049 0.04447\n",
      "starting to reduce usage for unit 4817 with usage 1.06261 . Total units tried = 50\n",
      "all done trying to reduce usage of unit 4817 final usage = 1.02886 1403 sec elapsed 18 1 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00049 0.04431\n",
      "starting to reduce usage for unit 3004 with usage 1.06108 . Total units tried = 51\n",
      "all done trying to reduce usage of unit 3004 final usage = 1.02976 1410 sec elapsed 14 0 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 1.00049 0.04418\n",
      "starting to reduce usage for unit 2826 with usage 1.06098 . Total units tried = 52\n",
      "try to drop unit 2826 from 20 th HD.  usage down to 1.036421382121671\n",
      "all done trying to reduce usage of unit 2826 final usage = 1.0282 1417 sec elapsed 18 0 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 1.00048 0.04399\n",
      "starting to reduce usage for unit 5908 with usage 1.0608 . Total units tried = 53\n",
      "try to drop unit 5908 from 16 th HD.  usage down to 1.0512376259474225\n",
      "all done trying to reduce usage of unit 5908 final usage = 1.02998 1442 sec elapsed 18 7 successful, failed patches, couldn't start= 6\n",
      "current avg and SD of usage are 1.00048 0.04386\n",
      "starting to reduce usage for unit 4311 with usage 1.05954 . Total units tried = 54\n",
      "try to drop unit 4311 from 7 th HD.  usage down to 1.0532051156454927\n",
      "try to drop unit 4311 from 14 th HD.  usage down to 1.0512983429637568\n",
      "try to drop unit 4311 from 21 th HD.  usage down to 1.0450884132340144\n",
      "try to drop unit 4311 from 28 th HD.  usage down to 1.037741654263129\n",
      "all done trying to reduce usage of unit 4311 final usage = 1.02921 1458 sec elapsed 19 0 successful, failed patches, couldn't start= 13\n",
      "current avg and SD of usage are 1.00048 0.0437\n",
      "starting to reduce usage for unit 2311 with usage 1.05935 . Total units tried = 55\n",
      "all done trying to reduce usage of unit 2311 final usage = 1.02851 1465 sec elapsed 12 1 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00048 0.04359\n",
      "starting to reduce usage for unit 3931 with usage 1.05843 . Total units tried = 56\n",
      "all done trying to reduce usage of unit 3931 final usage = 1.02825 1472 sec elapsed 12 0 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 1.00047 0.04348\n",
      "starting to reduce usage for unit 1253 with usage 1.06293 . Total units tried = 57\n",
      "all done trying to reduce usage of unit 1253 final usage = 1.0284 1477 sec elapsed 13 0 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 1.00047 0.04332\n",
      "starting to reduce usage for unit 2444 with usage 1.0577 . Total units tried = 58\n",
      "all done trying to reduce usage of unit 2444 final usage = 1.02945 1482 sec elapsed 12 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00047 0.0432\n",
      "starting to reduce usage for unit 231 with usage 1.05761 . Total units tried = 59\n",
      "all done trying to reduce usage of unit 231 final usage = 1.02964 1490 sec elapsed 16 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00046 0.0431\n",
      "starting to reduce usage for unit 2820 with usage 1.05751 . Total units tried = 60\n",
      "all done trying to reduce usage of unit 2820 final usage = 1.02738 1494 sec elapsed 12 0 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 1.00046 0.04299\n",
      "starting to reduce usage for unit 5802 with usage 1.05738 . Total units tried = 61\n",
      "try to drop unit 5802 from 22 th HD.  usage down to 1.0471799206673824\n",
      "all done trying to reduce usage of unit 5802 final usage = 1.02849 1538 sec elapsed 14 20 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 1.00046 0.04284\n",
      "starting to reduce usage for unit 2578 with usage 1.05724 . Total units tried = 62\n",
      "try to drop unit 2578 from 23 th HD.  usage down to 1.0433185768017104\n",
      "all done trying to reduce usage of unit 2578 final usage = 1.0298 1550 sec elapsed 14 0 successful, failed patches, couldn't start= 17\n",
      "current avg and SD of usage are 1.00045 0.04275\n",
      "starting to reduce usage for unit 645 with usage 1.05741 . Total units tried = 63\n",
      "try to drop unit 645 from 18 th HD.  usage down to 1.0309000091936504\n",
      "all done trying to reduce usage of unit 645 final usage = 1.02861 1563 sec elapsed 14 1 successful, failed patches, couldn't start= 3\n",
      "current avg and SD of usage are 1.00045 0.04264\n",
      "starting to reduce usage for unit 2416 with usage 1.05629 . Total units tried = 64\n",
      "all done trying to reduce usage of unit 2416 final usage = 1.02951 1575 sec elapsed 13 0 successful, failed patches, couldn't start= 10\n",
      "current avg and SD of usage are 1.00045 0.04255\n",
      "starting to reduce usage for unit 5805 with usage 1.05691 . Total units tried = 65\n",
      "all done trying to reduce usage of unit 5805 final usage = 1.02986 1603 sec elapsed 18 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00045 0.04243\n",
      "starting to reduce usage for unit 3308 with usage 1.05624 . Total units tried = 66\n",
      "all done trying to reduce usage of unit 3308 final usage = 1.02819 1607 sec elapsed 14 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00045 0.04235\n",
      "starting to reduce usage for unit 2659 with usage 1.05624 . Total units tried = 67\n",
      "all done trying to reduce usage of unit 2659 final usage = 1.02877 1617 sec elapsed 14 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00045 0.04228\n",
      "starting to reduce usage for unit 4730 with usage 1.05553 . Total units tried = 68\n",
      "try to drop unit 4730 from 20 th HD.  usage down to 1.0325342012277936\n",
      "all done trying to reduce usage of unit 4730 final usage = 1.02762 1643 sec elapsed 12 10 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00045 0.04213\n",
      "starting to reduce usage for unit 159 with usage 1.055 . Total units tried = 69\n",
      "all done trying to reduce usage of unit 159 final usage = 1.02894 1652 sec elapsed 16 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00044 0.04205\n",
      "starting to reduce usage for unit 1291 with usage 1.05493 . Total units tried = 70\n",
      "all done trying to reduce usage of unit 1291 final usage = 1.02956 1658 sec elapsed 11 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00044 0.04194\n",
      "starting to reduce usage for unit 87 with usage 1.05431 . Total units tried = 71\n",
      "all done trying to reduce usage of unit 87 final usage = 1.02811 1665 sec elapsed 12 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00044 0.04186\n",
      "starting to reduce usage for unit 4534 with usage 1.05371 . Total units tried = 72\n",
      "all done trying to reduce usage of unit 4534 final usage = 1.02028 1670 sec elapsed 3 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00044 0.04163\n",
      "starting to reduce usage for unit 2642 with usage 1.05326 . Total units tried = 73\n",
      "all done trying to reduce usage of unit 2642 final usage = 1.02865 1688 sec elapsed 12 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00044 0.04155\n",
      "starting to reduce usage for unit 4851 with usage 1.05297 . Total units tried = 74\n",
      "all done trying to reduce usage of unit 4851 final usage = 1.02823 1715 sec elapsed 16 0 successful, failed patches, couldn't start= 3\n",
      "current avg and SD of usage are 1.00044 0.04144\n",
      "starting to reduce usage for unit 3689 with usage 1.05412 . Total units tried = 75\n",
      "all done trying to reduce usage of unit 3689 final usage = 1.02721 1733 sec elapsed 14 1 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 1.00044 0.04132\n",
      "starting to reduce usage for unit 5596 with usage 1.05185 . Total units tried = 76\n",
      "all done trying to reduce usage of unit 5596 final usage = 1.02877 1741 sec elapsed 14 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00043 0.04126\n",
      "starting to reduce usage for unit 235 with usage 1.05156 . Total units tried = 77\n",
      "all done trying to reduce usage of unit 235 final usage = 1.02888 1758 sec elapsed 16 1 successful, failed patches, couldn't start= 9\n",
      "current avg and SD of usage are 1.00043 0.04119\n",
      "starting to reduce usage for unit 3384 with usage 1.05131 . Total units tried = 78\n",
      "try to drop unit 3384 from 37 th HD.  usage down to 1.0358413408383977\n",
      "all done trying to reduce usage of unit 3384 final usage = 1.02834 1778 sec elapsed 12 3 successful, failed patches, couldn't start= 24\n",
      "current avg and SD of usage are 1.00043 0.04113\n",
      "starting to reduce usage for unit 2970 with usage 1.05123 . Total units tried = 79\n",
      "try to drop unit 2970 from 15 th HD.  usage down to 1.0372081196305802\n",
      "all done trying to reduce usage of unit 2970 final usage = 1.02843 1784 sec elapsed 9 1 successful, failed patches, couldn't start= 7\n",
      "current avg and SD of usage are 1.00043 0.04103\n",
      "starting to reduce usage for unit 5810 with usage 1.05006 . Total units tried = 80\n",
      "try to drop unit 5810 from 24 th HD.  usage down to 1.043224271648788\n",
      "all done trying to reduce usage of unit 5810 final usage = 1.02961 1804 sec elapsed 14 22 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 1.00043 0.04094\n",
      "starting to reduce usage for unit 4029 with usage 1.04961 . Total units tried = 81\n",
      "all done trying to reduce usage of unit 4029 final usage = 1.02958 1811 sec elapsed 11 0 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 1.00043 0.04086\n",
      "starting to reduce usage for unit 4822 with usage 1.04904 . Total units tried = 82\n",
      "all done trying to reduce usage of unit 4822 final usage = 1.02865 1830 sec elapsed 10 5 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 1.00043 0.04074\n",
      "starting to reduce usage for unit 1201 with usage 1.04904 . Total units tried = 83\n",
      "all done trying to reduce usage of unit 1201 final usage = 1.02836 1834 sec elapsed 11 0 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 1.00043 0.04063\n",
      "starting to reduce usage for unit 2432 with usage 1.04807 . Total units tried = 84\n",
      "all done trying to reduce usage of unit 2432 final usage = 1.02968 1841 sec elapsed 9 0 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 1.00042 0.04056\n",
      "starting to reduce usage for unit 20 with usage 1.04804 . Total units tried = 85\n",
      "all done trying to reduce usage of unit 20 final usage = 1.02941 1850 sec elapsed 13 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00042 0.0405\n",
      "starting to reduce usage for unit 2782 with usage 1.04795 . Total units tried = 86\n",
      "all done trying to reduce usage of unit 2782 final usage = 1.02899 1854 sec elapsed 9 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00042 0.0404\n",
      "starting to reduce usage for unit 240 with usage 1.04778 . Total units tried = 87\n",
      "all done trying to reduce usage of unit 240 final usage = 1.02937 1867 sec elapsed 12 0 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 1.00042 0.04034\n",
      "starting to reduce usage for unit 2407 with usage 1.04755 . Total units tried = 88\n",
      "all done trying to reduce usage of unit 2407 final usage = 1.02809 1879 sec elapsed 12 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00042 0.04028\n",
      "starting to reduce usage for unit 4111 with usage 1.04863 . Total units tried = 89\n",
      "all done trying to reduce usage of unit 4111 final usage = 1.0247 1884 sec elapsed 5 0 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 1.00042 0.04016\n",
      "starting to reduce usage for unit 4805 with usage 1.0508 . Total units tried = 90\n",
      "try to drop unit 4805 from 22 th HD.  usage down to 1.032322337596509\n",
      "all done trying to reduce usage of unit 4805 final usage = 1.02904 1902 sec elapsed 12 4 successful, failed patches, couldn't start= 8\n",
      "current avg and SD of usage are 1.00042 0.04004\n",
      "starting to reduce usage for unit 2748 with usage 1.04722 . Total units tried = 91\n",
      "all done trying to reduce usage of unit 2748 final usage = 1.02973 1910 sec elapsed 9 0 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00042 0.03994\n"
     ]
    }
   ],
   "source": [
    "#SECOND PATCHING BLOCK -- OVERUSERS.  applies a suppression of LONG STRINGS.  run second for most states except MA\n",
    "maxSD = 0.04 #0.06  #0.08\n",
    "stopMaxUse = 1.+  2.* maxSD  #0.5*maxSD  #don't be too aggressive; may create long chains\n",
    "print(\"default use threshold for moving on to next overused unit is\",r5(stopMaxUse) )\n",
    "stopMaxUse = float(input(\"enter updated stopMaxUse value\"))\n",
    "nInPlay = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > stopMaxUse:\n",
    "        nInPlay +=1\n",
    "print(\"there are currently\",nInPlay,\"units out of\",nUnits,\"with usage above\",stopMaxUse)\n",
    "nBigUsers = 5\n",
    "maxExchangePop = 0.05*aDP\n",
    "print(\"maxExchangePop is currently\",r5(maxExchangePop/aDP),\"fraction of avgDistrictPop\")\n",
    "newMEPratio = float(input(\"Enter updated maxExchangePop fraction\"))\n",
    "maxExchangePop = newMEPratio*aDP \n",
    "print(\"this block reduces overuse, with exchanges up to\",int(maxExchangePop)) #1/25/24\n",
    "maxGap = 0.9 * np.median(unitPop) \n",
    "maxNtries = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > stopMaxUse:\n",
    "        maxNtries +=1\n",
    "#maxNtries = int(currSD * nUnits / nDistricts)   #try up to about 10% of the districts a unit is drawn into\n",
    "#maxNtries = 10 #overrirde\n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "attemptedBigUs = list()\n",
    "print(\"current avg and SD of unit usage are\",r5(currAvg), r5(currSD),\". Now trying to reduce up to\",maxNtries,\"units' overusage\" )\n",
    "startTime = time.time()\n",
    "while currSD > maxSD and len(attemptedBigUs) < maxNtries: \n",
    "    #each round, find the (5) most overused not-yet-tried units. Pick the unit w/ most overuse of it + 1-nbrs\n",
    "    idx = np.argsort(unitUse)\n",
    "    idxNo, nBigFound, bigUsers = 0,0,list()\n",
    "    while nBigFound < nBigUsers:\n",
    "        consideredBigU = idx[-idxNo-1]\n",
    "        if consideredBigU not in attemptedBigUs:\n",
    "            bigUsers.append(consideredBigU)\n",
    "            nBigFound +=1\n",
    "        idxNo +=1\n",
    "    OUUclusters = [ [b] + unitNbrs[b] for b in bigUsers ]\n",
    "    bigOverUse = [np.sum([(unitUse[j] - 1.) for j in OUUclusters[i] ]) for i in range(nBigUsers) ]\n",
    "    bigI = bigOverUse.index(np.max(bigOverUse))\n",
    "    OUU = bigUsers[ bigI ]  #pick the unit that centers cluster with most overuse\n",
    "    attemptedBigUs.append(OUU)  #so we don't try this unit again in a future loop\n",
    "    OUUc = OUUclusters[bigI]  #the list of this unit and ALL its neighbors (to be curated below ...)\n",
    "    print(\"starting to reduce usage for unit\",OUU,\"with usage\",r5(unitUse[OUU]),\". Total units tried =\",len(attemptedBigUs) )\n",
    "    for u in OUUc.copy():\n",
    "        if unitUse[u] < 1.:\n",
    "            OUUc.remove(u)  #...drop any underused neighbors of the primary OUU from the target sheddable cluster\n",
    "    OUU2nbrSet = set( unitNbrs[OUU])\n",
    "    for u in OUUc:\n",
    "        OUU2nbrSet = OUU2nbrSet.union(set(unitNbrs[u])) \n",
    "    for u in OUUc:\n",
    "        OUU2nbrSet = OUU2nbrSet.difference({u})\n",
    "    ouuHDs, ouuDists = list(), list()\n",
    "    for t in popHDlist:  #finding all HDs with at least one cluster member on the boundary\n",
    "        if OUU in HDunitList[t]:\n",
    "            HDadjoinSet = set( getAdjoiners(HDunitList[t],unitNbrs) )\n",
    "            if len(HDadjoinSet.intersection(OUU2nbrSet) ) > 0: #the OUU or one of its overused 1-neighbors adjoins the complement\n",
    "                ouuHDs.append(t)  #so we can shed the OOUc to the complement\n",
    "                ouuDists.append( unitCP[OUU].distance(hdCP[t]) / avgDist[t] )\n",
    "    nPatchSuccess, nPatchFail, nCouldntStart, idxNo, idx0 = 0, 0, 0, 0, np.argsort(ouuDists)\n",
    "    while unitUse[OUU] > stopMaxUse and idxNo > -0.5*len(ouuHDs): #arbitrarily only examine 50% of HDs, biasing farthest ones\n",
    "        idxNo -=1\n",
    "        if idxNo % int(0.1*len(ouuHDs)) == 0:\n",
    "            print(\"try to drop unit\",OUU,\"from\",abs(idxNo),\"th HD.  usage down to\",unitUse[OUU] )\n",
    "        t = ouuHDs[idx0[idxNo]]\n",
    "        trySet = set(HDunitList[t]).difference(set(OUUc))\n",
    "        contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        if not (contig and complementContig):  #dropping the cluster creates a problem (likely an HD discontig).  Try something simpler ...\n",
    "            if len(set(unitNbrs[OUU]).intersection(HDadjoinSet) )  > 0:  #Yay! The OUU itself on border.  Try dropping just it, not the full cluster\n",
    "                HDouuSet = {OUU}\n",
    "                trySet = set(HDunitList[t]).difference( {OUU} )\n",
    "                contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        else:\n",
    "            HDouuSet = set(HDunitList[t]).intersection(set(OUUc))\n",
    "        if contig and complementContig:  #we can at least drop the cluster, let's go for more\n",
    "            #HDouuSet = set(HDunitList[t]).intersection(set(OUUc))  #the subset of the OUU cluster that's in this HD.  Defined above\n",
    "            HDouuCpop = np.sum([unitPop[u] for u in HDouuSet])\n",
    "            giveUpOnShedding = False            \n",
    "            shedCandidates, shedScores = list(), list()\n",
    "            bdryCandidates = getBdryNonEdgers(trySet, unitNbrs)  #new - any boundary unit can be shed, even if far from OUUc\n",
    "            for u in bdryCandidates:\n",
    "                if HDouuCpop + unitPop[u] <= maxExchangePop:\n",
    "                    shedCandidates.append(u)\n",
    "                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])  #bias toward far, overused\n",
    "            if len(shedCandidates) == 0:\n",
    "                giveUpOnShedding = True\n",
    "            while HDouuCpop < maxExchangePop and not giveUpOnShedding:\n",
    "                idx, ij, notYetPicked = np.argsort(shedScores), 0, True\n",
    "                while ij < len(shedScores) and notYetPicked:\n",
    "                    listNo = idx[-1-ij]   #work from high to low score\n",
    "                    shedU = shedCandidates[listNo]\n",
    "                    if shedScores[listNo] <= 0:  #we're delving into the underused; stop adding to shed list\n",
    "                        break\n",
    "                    contig,cContig, __, ___ = enclaveCheck(list(trySet.difference({shedU}) ), unitNbrs)\n",
    "                    if contig and cContig:\n",
    "                        notYetPicked = False\n",
    "                        HDouuCpop += unitPop[shedU]\n",
    "                        #print(\"shedding unit\",shedU,\"from HD\",t,\"total shed Pop now\", HDouuCpop)\n",
    "                        HDouuSet.add(shedU)\n",
    "                        trySet.remove(shedU)\n",
    "                        del shedScores[shedCandidates.index(shedU)]\n",
    "                        del shedCandidates[shedCandidates.index(shedU)]\n",
    "                        newSheddables = set(unitNbrs[shedU]).intersection(trySet)\n",
    "                        for u in newSheddables:\n",
    "                            if HDouuCpop + unitPop[u] <= maxExchangePop and u not in shedCandidates:\n",
    "                                shedCandidates.append(u)\n",
    "                                shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnShedding = True  #all candidates would create a discontig, so can't shed any more units\n",
    "            shedSet = HDouuSet.copy()  #set(OUUc).intersection(set(HDunitList[t]))\n",
    "            trySet = set(HDunitList[t]).difference(shedSet) \n",
    "            gap = aDP - np.sum([unitPop[u] for u in trySet])\n",
    "            nearHDlist, nearHDscore = list(), list()  #these will be dynamic lists of the nearby underused units\n",
    "            for u in trySet:\n",
    "                for uu in unitNbrs[u]:\n",
    "                    if uu not in HDunitList[t] and uu not in nearHDlist and unitPop[uu] < gap + maxGap and unitUse[uu] < 1.01:\n",
    "                        nearHDlist.append(uu)\n",
    "                        nearHDscore.append(5.*(unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )\n",
    "                        #bias toward UNDERUSED, close\n",
    "            addedSet = set( )    \n",
    "            stillGoing = True \n",
    "            while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "                nearHDscore2 = nearHDscore.copy()\n",
    "                for ij, uu in enumerate(nearHDlist):\n",
    "                    nHDnbrs = len( set(unitNbrs[uu]).intersection(trySet) )\n",
    "                    if nHDnbrs == 1 :  #BIAS AGAINST CREATING A SLIM CHAIN\n",
    "                        nearHDscore2[ij] *= 0.5   #make this score closer to zero (less negative)  #NEW FOR GA 3/11/24\n",
    "                idx, ij, notYetPicked = np.argsort(nearHDscore2), 0, True   #originally, used nearHDscore itself here\n",
    "                while ij < len(nearHDscore) and notYetPicked:        \n",
    "                    listNo = idx[ij]   #nearHDscore.index(np.min(nearHDscore))\n",
    "                    unitNoToAdd = nearHDlist[listNo]  #add this unit ...                            \n",
    "                    canAdd  = wontEnclave(unitNoToAdd, list(trySet), unitNbrs, borderUnits)\n",
    "                    if canAdd:\n",
    "                        notYetPicked = False\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    stillGoing = False  #can't add any more units; we can't without creating an enclave\n",
    "                else:\n",
    "                    gap -= unitPop[unitNoToAdd]\n",
    "                    addedSet.add(unitNoToAdd)\n",
    "                    trySet.add( unitNoToAdd)\n",
    "                    for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                        if uu not in trySet and uu not in nearHDlist and unitPop[uu] < gap + maxGap and unitUse[uu] < 1.01:  \n",
    "                            nearHDlist.append(uu)\n",
    "                            nearHDscore.append(5.* (unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] ) \n",
    "                            #bias toward UNDERUSED, ~close\n",
    "                    del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "                    del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "                    for ijj, uu in enumerate(nearHDlist.copy()):\n",
    "                        if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                            del nearHDscore[nearHDlist.index(uu)]\n",
    "                            del nearHDlist[ nearHDlist.index(uu)]\n",
    "            currPop = np.sum([unitPop[u] for u in trySet])\n",
    "            if abs(currPop - aDP) <= 2.* maxGap:\n",
    "                for u in shedSet:\n",
    "                    unitUse[u] -= HDweight[t] * nDistricts\n",
    "                for u in addedSet:\n",
    "                    unitUse[u] += HDweight[t] * nDistricts\n",
    "                HDunitList[t] = list(trySet)\n",
    "                HDvPop[t]    = currPop\n",
    "                nPatchSuccess +=1\n",
    "            else:\n",
    "                nPatchFail +=1\n",
    "            # end of shed + add patching on this HD\n",
    "            #print(\"shed and patched for HD, OUU\",t,OUU)\n",
    "        else:\n",
    "            nCouldntStart +=1\n",
    "            #print(\"Due to discontiguity, can't drop OUU cluster for HD, OUU\", t, OUU)\n",
    "    print(\"all done trying to reduce usage of unit\",OUU,\"final usage =\",r5(unitUse[OUU]),int(time.time()-startTime),\"sec elapsed\",\n",
    "         nPatchSuccess,nPatchFail,\"successful, failed patches, couldn't start=\",nCouldntStart)\n",
    "    currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "    print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )\n",
    "            \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "92f90621-e7fc-4891-a5cd-69033c3c48e6",
   "metadata": {},
   "outputs": [],
   "source": [
    "#copy one of two above blocks and run again if needed (n/a for NC)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "cb60da52-ca13-45dd-8bf0-475213183a0d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "overused units\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "underused units\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"overused units\")\n",
    "maxPlot = 1.06\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > maxPlot:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(round(unitUse[u],2),unitGeom[u])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()\n",
    "print(\"underused units\")\n",
    "minPlot = 0.94\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < minPlot:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(round(unitUse[u],2),unitGeom[u])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fa912158-e8e9-46f3-8c3d-f6b17c26e62c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Note - for MA, above is second run-through after overuse, then underuse pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "0d4f1372-6044-4803-91d9-de4b95a40083",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unpatched, patched use avgs are 1.00096 1.00042 and their SDs are 0.09746 0.03994\n",
      "And here is the pop distro\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 0 out of 6361\n",
      "working on HD 300 out of 6361\n",
      "working on HD 600 out of 6361\n",
      "working on HD 900 out of 6361\n",
      "working on HD 1200 out of 6361\n",
      "working on HD 1500 out of 6361\n",
      "working on HD 1800 out of 6361\n",
      "working on HD 2100 out of 6361\n",
      "working on HD 2400 out of 6361\n",
      "working on HD 2700 out of 6361\n",
      "working on HD 3000 out of 6361\n",
      "working on HD 3300 out of 6361\n",
      "working on HD 3600 out of 6361\n",
      "working on HD 3900 out of 6361\n",
      "working on HD 4200 out of 6361\n",
      "working on HD 4500 out of 6361\n",
      "working on HD 4800 out of 6361\n",
      "working on HD 5100 out of 6361\n",
      "working on HD 5400 out of 6361\n",
      "working on HD 5700 out of 6361\n",
      "working on HD 6000 out of 6361\n",
      "working on HD 6300 out of 6361\n",
      "all done checking HD and complement contiguity for all 6361 HDs\n"
     ]
    }
   ],
   "source": [
    "patchedUse, unpUse = [0.]*nUnits, [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        patchedUse[u] += HDweight[t] * nDistricts\n",
    "    for u in unpatchedHDlist[t]:\n",
    "        unpUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(patchedUse,bins=50, label=\"patched\",histtype=\"step\")\n",
    "plt.hist(unpUse, bins=50, label=\"unpatched\",histtype=\"step\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "patchedAvg, patchedSD = getWeightedAvgAndSD(patchedUse,unitPop)\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unpUse,unitPop)\n",
    "print(\"unpatched, patched use avgs are\",r5(unpatchedAvg), r5(patchedAvg),\"and their SDs are\",r5(unpatchedSD), r5(patchedSD) )\n",
    "print(\"And here is the pop distro\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP, ls=\"--\",color=\"orange\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "for t in popHDlist:\n",
    "    if t%300 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs)  #these HDunitLists now appear to be sets\n",
    "    if not unbroken or not noEnclave:\n",
    "        print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "ac9cd133-94f0-494b-ac74-0c584482d97e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lets write these UNIT lists to a file\n"
     ]
    }
   ],
   "source": [
    "print(\"Lets write these UNIT lists to a file\")\n",
    "HDvPop = [0. for t in range(nHDs)]  #writing UNIT lists to a file\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"fullyPatched.csv\" #\"contigUnpatchedB.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "id": "26b87c95-101f-4f8f-bb73-feb1827ac6b5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 if there were NO fragmented VTDs 0\n"
     ]
    }
   ],
   "source": [
    "noFrag = int(input(\"enter 1 if there were NO fragmented VTDs\"))\n",
    "if noFrag == 1:\n",
    "    nFragmentedVTDs,fragmentedVTDs = 0, list()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "ec102553-e4f3-4010-86bc-725a01b95788",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjAAAAGdCAYAAAAMm0nCAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/H5lhTAAAACXBIWXMAAA9hAAAPYQGoP6dpAAA/2ElEQVR4nO3de3TU1b3//1fuF2AmcslNblEQSIPKpcAcxLN6jASMnlqwX7GIVBF/cIItYBGwlttSwsKeVm0Fqp4Wj5dasccLBII5QcBqBAwiBBBRg6AwCTYmA0qu8/n9wcnIQIAk7Ezm8nysNWs189nZ2Z9PMfPKfn/2/oRZlmUJAAAggIS39wAAAABaigADAAACDgEGAAAEHAIMAAAIOAQYAAAQcAgwAAAg4BBgAABAwCHAAACAgBPZ3gNoK263W0ePHlWnTp0UFhbW3sMBAADNYFmWTpw4odTUVIWHn3+eJWgDzNGjR9WjR4/2HgYAAGiFI0eOqHv37uc9HrQBplOnTpJOXwCbzdbOowEAAM3hcrnUo0cPz+f4+QRtgGksG9lsNgIMAAAB5mK3f3ATLwAACDgEGAAAEHAIMAAAIOAQYAAAQMAhwAAAgIBDgAEAAAGHAAMAAAIOAQYAAAScoN3IDgAAmNXgtrS9tELlJ6qV2ClWw9I6KyK8fZ43SIABAAAX9cyWz/Xohv1e7yXZYrT433+gMRkpPh8PJSQAAHBeVd/Vqfe8vHPCiySVuWo07YWdyi855vNxEWAAAECTRuYW6polb120Xc5LO9Xgtnwwou8RYAAAwDl6z8vTV1XVzWrb4Jbe/ri8jUfkjQADAAA8GktGLfVo3r42GM35cRMvAACQJI1cVqivKps363K2quo6w6O5MAIMAABo1ayL1/d3jjc0kuahhAQAQAhrbcnobBNH9L70wbQAMzAAAISoSykZne2RvH26ddDlPtvYjhkYAABCUO95ecbCiyR9812d3v/8n8b6uxgCDAAAIcRUyagpRZ/5LsBQQgIAIESMzC1s9t4ureO7zewIMAAAhIC2mnU5k+OKrm3+MxpRQgIAIIi1ZcnoTAnxURpxZZc2/zmNCDAAAASp5j7LqDlW3Tn4gseXjRvosxVIEgEGAICg0+C2WvQsowtJjJcOLcvWmIwUrbpzsJJtMV7Hk20xWnXnYI3JSLnkn9US3AMDAEAQWfPBEc15dbeRvj5aMFr2+CjP12MyUnRjerK2l1ao/ES1EjvFalhaZ5/OvDQiwAAAECQyFuTrZG2Dkb4OLctu8v2I8DA5fHivy/lQQgIAIMA1loxMhJducecPL/6kxQHmq6++0p133qkuXbooLi5OAwcO1AcffOA5blmWFixYoJSUFMXFxSkzM1MHDx706qOiokITJ06UzWZTQkKCpkyZopMnT3q12b17t0aNGqXY2Fj16NFDy5cvb+UpAgAQvP5e/KWufGi9kb4+WjBaOxb6f3iRWhhgvvnmG40cOVJRUVHasGGD9u3bp//8z//UZZdd5mmzfPlyPfnkk1q1apW2bdumDh06KCsrS9XV399INHHiRO3du1cFBQVat26dtm7dqvvuu89z3OVyafTo0erVq5eKi4v12GOPadGiRXr66acNnDIAAMFh8JK39MCaj4z0dWhZttf9Lv4uzLKsZm+bN2/ePL377rt65513mjxuWZZSU1P1wAMP6Fe/+pUkqaqqSklJSVq9erUmTJig/fv3Kz09XTt27NDQoUMlSfn5+brpppv05ZdfKjU1VStXrtSvf/1rOZ1ORUdHe37266+/ro8//rhZY3W5XLLb7aqqqpLNZmvuKQIA4Pca3JaxWZe+XaJUMGe0kb5MaO7nd4tmYN58800NHTpUP/3pT5WYmKhBgwbpmWee8RwvLS2V0+lUZmam5z273a7hw4erqKhIklRUVKSEhARPeJGkzMxMhYeHa9u2bZ42119/vSe8SFJWVpYOHDigb775psmx1dTUyOVyeb0AAAg2az44Yiy8lCzK8qvw0hItCjCff/65Vq5cqb59+2rjxo2aPn26fvGLX+i5556TJDmdTklSUlKS1/clJSV5jjmdTiUmJnodj4yMVOfOnb3aNNXHmT/jbLm5ubLb7Z5Xjx49WnJqAAD4vYwF+caWSB9alq2OsYG7GLlFAcbtdmvw4MFaunSpBg0apPvuu09Tp07VqlWr2mp8zTZ//nxVVVV5XkeOHGnvIQEAYITJVUZ9u0QFxCqji2lR9EpJSVF6errXewMGDNDf//53SVJycrIkqaysTCkp3+/IV1ZWpmuvvdbTpry83KuP+vp6VVRUeL4/OTlZZWVlXm0av25sc7aYmBjFxMQ0eQwAgEBlcmO6kkVZAT3rcqYWzcCMHDlSBw4c8Hrvk08+Ua9evSRJaWlpSk5OVmFhoee4y+XStm3b5HA4JEkOh0OVlZUqLi72tNm0aZPcbreGDx/uabN161bV1dV52hQUFKhfv35eK54AAAhmlIzOr0UBZtasWXr//fe1dOlSffrpp3rppZf09NNPKycnR5IUFhammTNn6pFHHtGbb76pPXv26K677lJqaqpuvfVWSadnbMaMGaOpU6dq+/btevfddzVjxgxNmDBBqampkqSf/exnio6O1pQpU7R371797W9/0xNPPKHZs2ebPXsAAPyQyZLRVV2jg6JkdLYWLaOWpHXr1mn+/Pk6ePCg0tLSNHv2bE2dOtVz3LIsLVy4UE8//bQqKyt13XXXacWKFbrqqqs8bSoqKjRjxgytXbtW4eHhGj9+vJ588kl17NjR02b37t3KycnRjh071LVrV91///2aO3dus8fJMmoAQCAK9ZJRcz+/WxxgAgUBBgAQaHzxLCN/1yb7wAAAAPNq692sMmqhwJpXAgAgyPzmtRI9v+0LI30FYsmotULjLAEA8EN9HlqvereZOzlCYdblTJSQAADwscZVRibCS6iUjM7GDAwAAD4U6quMTAnNswYAoB2wysgcSkgAALQxk6uMRl1hC/nwIjEDAwBAmzK5ymj/kjGKi44w0legI8AAANBG+j60XnWsMmoTlJAAADCssWRkIrxQMmoaMzAAABhEycg3CDAAABjCxnS+QwkJAIBLdKq2wdjGdNdfaSe8NAMzMAAAXILJ/7VdWw4eN9IXJaPmI8AAANBKV8zPk6GKEbMuLUQJCQCAFmosGZkIL6wyah1mYAAAaIFJz27TO59+baQvSkatR4ABAKCZ0ublyVDFiFmXS0QJCQCAi2jcmM5EeKFkZAYzMAAAXAAb0/knAgwAAOfBxnT+iwADAMBZTtU2aMCCfCN93TE8Vbk/GWSkL39QW+/W80WH9EXFd+rVOV6THL0VHen7O1IIMAAAnMHkKqNPHhnbLh/ubSV3/T49806p1/LxR9fv19RRaZp/U7pPx0KAAQDg/7DK6Pxy1+/Tn7aWnvO+25LnfV+GmOCJhQAAtFLjxnQmwssdw1ODLrzU1rv1zDvnhpczPfNOqWrr3T4aETMwAIAQR8no4p4vOnTRXYfd1ul2U0Zd4ZMxEWAAACGLklHzlH79rdF2JgRfTAQA4CJOVtcbKxn9a5+EoA4vklTmqjbazgRmYAAAIWXs41u133nCSF+hsjFdN1uM0XYmEGAAACGj97w8Y30F+6zLma7s2tFoOxMoIQEAgl5jyciEYFxldDGTHL0VHnbhNuFhp9v5CjMwAICgZrJkFKyrjC4mOjJcU0elNbkPTKOpo9J8em0IMACAoEXJyJzGTerO3ok3PEztshNvmGVZplaQ+RWXyyW73a6qqirZbLb2Hg4AwId4llHbaetnITX385sZGABAUGFjurYVHRnus83qLoQAAwAIGqY2pouQ9FmIl4zOp8FtaXtphcpPVCuxU6yGpXVWxMXu8G0DBBgAQMA7WV2vjEUbjfT123EZum1YLyN9BZv8kmNavHafjlV9v2Fdij1WC29J15iMFJ+OhQADAAhoYx/fov3Ok0b6+mzpTe0ymxAI8kuOafoLO8+Z4XJWVWv6Czu18s7BPg0xFPYAAAGr97w8I+ElQqdXGRFemtbgtrR47b4my3ON7y1eu08NF3vio0EEGABAwDG5Md1vx2Vwv8tFbC+t8Cobnc2SdKyqWttLK3w2JkpIAICAQsnI98pPNO8hjc1tZwIBBgAQMNiYrn0kdoo12s6EFpWQFi1apLCwMK9X//79Pcerq6uVk5OjLl26qGPHjho/frzKysq8+jh8+LCys7MVHx+vxMREzZkzR/X19V5tNm/erMGDBysmJkZ9+vTR6tWrW3+GAICAV/VdnbHwMnHE5YSXFhqW1lkp9lidb64qTKdXIw1L6+yzMbV4BuYHP/iB/vd///f7DiK/72LWrFnKy8vTmjVrZLfbNWPGDI0bN07vvvuuJKmhoUHZ2dlKTk7We++9p2PHjumuu+5SVFSUli5dKkkqLS1Vdna2pk2bphdffFGFhYW69957lZKSoqysrEs9XwBAgBm5rFBfVZopTbAxXetEhIdp4S3pmv7CToVJXjfzNoaahbek+7Qc16JHCSxatEivv/66du3adc6xqqoqdevWTS+99JJuu+02SdLHH3+sAQMGqKioSCNGjNCGDRt088036+jRo0pKSpIkrVq1SnPnztXx48cVHR2tuXPnKi8vTyUlJZ6+J0yYoMrKSuXnN39baB4lAACBz9SsCxvTmeGLfWDa7FECBw8eVGpqqmJjY+VwOJSbm6uePXuquLhYdXV1yszM9LTt37+/evbs6QkwRUVFGjhwoCe8SFJWVpamT5+uvXv3atCgQSoqKvLqo7HNzJkzLziumpoa1dTUeL52uVwtPTUAgJ9gYzr/NCYjRTemJwfeTrzDhw/X6tWr1a9fPx07dkyLFy/WqFGjVFJSIqfTqejoaCUkJHh9T1JSkpxOpyTJ6XR6hZfG443HLtTG5XLp1KlTiouLa3Jsubm5Wrx4cUtOBwDgh1hl5N8iwsPkuLJLew+jZQFm7Nixnv999dVXa/jw4erVq5deeeWV8wYLX5k/f75mz57t+drlcqlHjx7tOCIAQEuZKhlFSvqUklFQu6Q7mRISEnTVVVfp008/VXJysmpra1VZWenVpqysTMnJyZKk5OTkc1YlNX59sTY2m+2CISkmJkY2m83rBQAIDKY3piO8BL9LCjAnT57UZ599ppSUFA0ZMkRRUVEqLCz0HD9w4IAOHz4sh8MhSXI4HNqzZ4/Ky8s9bQoKCmSz2ZSenu5pc2YfjW0a+wAABJexj28xdr/LZ0tv4n6XENGiAPOrX/1KW7Zs0aFDh/Tee+/pJz/5iSIiInTHHXfIbrdrypQpmj17tt5++20VFxfr7rvvlsPh0IgRIyRJo0ePVnp6uiZNmqSPPvpIGzdu1MMPP6ycnBzFxMRIkqZNm6bPP/9cDz74oD7++GOtWLFCr7zyimbNmmX+7AEA7crUs4y6xfEso1DTontgvvzyS91xxx365z//qW7duum6667T+++/r27dukmSfv/73ys8PFzjx49XTU2NsrKytGLFCs/3R0REaN26dZo+fbocDoc6dOigyZMna8mSJZ42aWlpysvL06xZs/TEE0+oe/fuevbZZ9kDBgCCSNV3dbpmyVtG+vpowWjZ46OM9IXA0aJ9YAIJ+8AAgH8amVuory7wYMCWYEfd4NNm+8AAANBapm7U7RYn7VhIeAllBBgAQJujZATTCDAAgDZFyQhtgQADAGgTDW5LVz603khfHcKlvUsJL/geAQYAYNyaD45ozqu7jfT1u/EDNe6HPY30heBBgAEAGJWxIF8naxuM9MWzjPxPg9sKvIc5AgBwIawyCm75Jce0eO0+HTvjnqYUe6wW3pKuMRkpPh0LAQYAcMlYZRT88kuOafoLO3X25nHOqmpNf2GnVt452KchhgADALgkrDIKfg1uS4vX7jsnvEiSJSlM0uK1+3RjerLPykmX9DBHAEDoanBb6j0vz0h4SYwnvPiz7aUVXmWjs1mSjlVVa3tphc/GxAwMAKDF/l78pR5Y85GRvigZ+b/yE80Lqc1tZwIBBgDQIoOXvKWK7+qM9MWsS2BI7BRrtJ0JlJAAAM3SWDIyEV76dokivASQYWmdlWKP1fnubgnT6dVIw9I6+2xMBBgAwEWt+eCIsV11SxZlqWDOaCN9wTciwsO08JZ0STonxDR+vfCWdJ/uB0MJCQBwQSY3pmPWJXCNyUjRyjsHn7MPTDL7wAAA/InJZxn17RLFrEsQGJORohvTk9mJFwDgn0w+y6hkUZY6xvJxEywiwsPkuLJLew+DAAMA8EbJCIGAm3gBAJKk2nq3es/LMxJeWGWEtsYMDABAv3mtRM9v+8JIX5SM4Av8CwOAENf3ofWqczf1lJuWY9YFvkIJCQBCVOPGdCbCCyUj+BozMAAQglhlhEDHvzgACDGsMkIwoIQEACHC5Cqjq7pGE17QrpiBAYAQsOCNEv13EauMEDz4FwgAQa7/wxtUXe820hezLvAXlJAAIEg1loxMhJdRV9gIL/ArzMAAQBAyuTHd/iVjFBcdYaQvwBQCDAAEmT4PrVc9G9MhyFFCAoAg0VgyMhFeWGUEf8cMDAAEAZ5lhFDDv1AACHCUjBCKKCEBQIA6VdtgrGTEKiMEGmZgACAATf6v7dpy8LiRvlhlhEBEgAGAAHPl/Dw1mKkYMeuCgEUJCQACROMqIxPhhZIRAh0zMAAQANiYDvBGgAEAP8cqI+BclJAAwE+ZXGV0/ZV2wguCCjMwAOCHWGUEXBgBBgD8zBXz82SoYsSsC4LWJZWQli1bprCwMM2cOdPzXnV1tXJyctSlSxd17NhR48ePV1lZmdf3HT58WNnZ2YqPj1diYqLmzJmj+vp6rzabN2/W4MGDFRMToz59+mj16tWXMlQA8HuNJSMT4eWO4amEFwS1Vs/A7NixQ3/605909dVXe70/a9Ys5eXlac2aNbLb7ZoxY4bGjRund999V5LU0NCg7OxsJScn67333tOxY8d01113KSoqSkuXLpUklZaWKjs7W9OmTdOLL76owsJC3XvvvUpJSVFWVtYlnC4A+KdJz27TO59+baSvTx4Zq+hIbnFEcAuzLKvFWf/kyZMaPHiwVqxYoUceeUTXXnutHn/8cVVVValbt2566aWXdNttt0mSPv74Yw0YMEBFRUUaMWKENmzYoJtvvllHjx5VUlKSJGnVqlWaO3eujh8/rujoaM2dO1d5eXkqKSnx/MwJEyaosrJS+fn5zRqjy+WS3W5XVVWVbDZbS08RAHwmbV6eDFWMmHVBwGvu53erInpOTo6ys7OVmZnp9X5xcbHq6uq83u/fv7969uypoqIiSVJRUZEGDhzoCS+SlJWVJZfLpb1793ranN13VlaWp4+m1NTUyOVyeb0AwJ81loxMhBc2pkOoaXEJ6eWXX9bOnTu1Y8eOc445nU5FR0crISHB6/2kpCQ5nU5PmzPDS+PxxmMXauNyuXTq1CnFxcWd87Nzc3O1ePHilp4OALQLkyUjVhkhFLVoBubIkSP65S9/qRdffFGxsbFtNaZWmT9/vqqqqjyvI0eOtPeQAKBJafPyjIWXQ8uyCS8ISS0KMMXFxSovL9fgwYMVGRmpyMhIbdmyRU8++aQiIyOVlJSk2tpaVVZWen1fWVmZkpOTJUnJycnnrEpq/PpibWw2W5OzL5IUExMjm83m9QIAf2KyZMQqI4S6FpWQbrjhBu3Zs8frvbvvvlv9+/fX3Llz1aNHD0VFRamwsFDjx4+XJB04cECHDx+Ww+GQJDkcDj366KMqLy9XYmKiJKmgoEA2m03p6emeNuvXr/f6OQUFBZ4+ACDQsMoIMKtFAaZTp07KyMjweq9Dhw7q0qWL5/0pU6Zo9uzZ6ty5s2w2m+6//345HA6NGDFCkjR69Gilp6dr0qRJWr58uZxOpx5++GHl5OQoJiZGkjRt2jT98Y9/1IMPPqh77rlHmzZt0iuvvKK8vDwT5wwAPsUqI8A84zvx/v73v1d4eLjGjx+vmpoaZWVlacWKFZ7jERERWrdunaZPny6Hw6EOHTpo8uTJWrJkiadNWlqa8vLyNGvWLD3xxBPq3r27nn32WfaAARBQTtU2aMCC5m39cDF3DE9V7k8GGekLCAat2gcmELAPDID2RMkIaJ3mfn7zLCQAMIySEdD2iPQAYMjJ6npjq4wmjric8AJcADMwAGDA2Me3ar/zhJG+KBkBF0eAAYBL1HuemRWSEZI+Y9YFaBYCDAC00snqemUs2mikr9+Oy9Btw3oZ6QsIBQQYAGiFsY9v0X7nSSN9fbb0JkWEhxnpCwgVBBgAaCFTJSOJVUZAa3GXGAA0U+MqIxN4lhFwaZiBAYBmMFkyYpURcOkIMABwEawyAvwPAQYAzoNVRoD/IsAAQBNYZQT4NwIMAJyFkhHg/wgwAPB/KBkBgYMAAwCiZAQEGgIMgJBnqmTULU7asZCSEeALBBgAIavquzpds+QtI319tGC07PFRRvoCcHEEGAAhaeSyQn1VWW2kL3bUBXyPAAMg5JgqGXUIl/YuJbwA7YEAAyBkmCwZ/W78QI37YU8jfQFoOQIMgJAwMrdQX1WZKRmxyghofwQYAEGtwW3pyofWG+krUtKn3O8C+AUCDICg9ffiL/XAmo+M9MXGdIB/IcAACEqDl7yliu/qjPRFyQjwPwQYAEGHjemA4EeAARA02JgOCB0EGABBweQqIzamA/wfAQZAwKNkBIQeAgyAgEXJCAhdBBgAAYmSERDaCDAAAorJjen6dolSwZzRRvoC4FsEGAABY80HRzTn1d1G+ipZlKWOsfwKBAIV//UCCAgZC/J1srbBSF+UjIDAF97eAwCAC2lwW+o9L89IeEmMJ7wAwYIZGAB+y2TJiFVGQHAhwADwS5SMAP9UW+/W80WH9EXFd+rVOV6THL0VHen7gg4BBoBfqa1366qHNxjpKzFe2r6A8AKYkrt+n555p1Ru6/v3Hl2/X1NHpWn+Tek+HQsBBoDfWPhGiZ4r+sJIX5SMALNy1+/Tn7aWnvO+25LnfV+GGG7iBeAXMhbkGwsvh5ZlE14Ag2rr3XrmnXPDy5meeadUtfVuH42IAAOgnZlcZdS3SxT3uwBt4PmiQ15lo6a4rdPtfIUSEoB2w8Z0QGD4ouI7o+1M4L92AO2CVUZA4OjVOd5oOxNaVEJauXKlrr76atlsNtlsNjkcDm3Y8P1qgerqauXk5KhLly7q2LGjxo8fr7KyMq8+Dh8+rOzsbMXHxysxMVFz5sxRfX29V5vNmzdr8ODBiomJUZ8+fbR69erWnyEAv0LJCAg8kxy9FR524TbhYafb+UqLAkz37t21bNkyFRcX64MPPtC//du/6cc//rH27t0rSZo1a5bWrl2rNWvWaMuWLTp69KjGjRvn+f6GhgZlZ2ertrZW7733np577jmtXr1aCxYs8LQpLS1Vdna2fvSjH2nXrl2aOXOm7r33Xm3cuNHQKQNoL2s+OGLsQYwli7J4ECPgI9GR4Zo6Ku2CbaaOSvPpfjBhlmVd5LacC+vcubMee+wx3XbbberWrZteeukl3XbbbZKkjz/+WAMGDFBRUZFGjBihDRs26Oabb9bRo0eVlJQkSVq1apXmzp2r48ePKzo6WnPnzlVeXp5KSko8P2PChAmqrKxUfn5+s8flcrlkt9tVVVUlm812KacIwABKRkDga2ofmPAwGd0Hprmf362+B6ahoUFr1qzRt99+K4fDoeLiYtXV1SkzM9PTpn///urZs6cnwBQVFWngwIGe8CJJWVlZmj59uvbu3atBgwapqKjIq4/GNjNnzrzgeGpqalRTU+P52uVytfbUABhkcmO6UVfY9Px9o4z0BaDl5t+UrgdG9w/MnXj37Nkjh8Oh6upqdezYUa+99prS09O1a9cuRUdHKyEhwat9UlKSnE6nJMnpdHqFl8bjjccu1MblcunUqVOKi4trcly5ublavHhxS08HQBv6zWslen6bmb1d9i8Zo7joCCN9AWi96MhwTRl1RXsPo+UBpl+/ftq1a5eqqqr06quvavLkydqyZUtbjK1F5s+fr9mzZ3u+drlc6tGjRzuOCAhtfR9ar7qLbRzRTJSMAJytxQEmOjpaffr0kSQNGTJEO3bs0BNPPKHbb79dtbW1qqys9JqFKSsrU3JysiQpOTlZ27dv9+qvcZXSmW3OXrlUVlYmm8123tkXSYqJiVFMTExLTweAYSZLRn27RHGjLoAmXXLRyu12q6amRkOGDFFUVJQKCws9xw4cOKDDhw/L4XBIkhwOh/bs2aPy8nJPm4KCAtlsNqWnp3vanNlHY5vGPgD4r9+8VmIsvLDKCMCFtGgGZv78+Ro7dqx69uypEydO6KWXXtLmzZu1ceNG2e12TZkyRbNnz1bnzp1ls9l0//33y+FwaMSIEZKk0aNHKz09XZMmTdLy5cvldDr18MMPKycnxzN7Mm3aNP3xj3/Ugw8+qHvuuUebNm3SK6+8ory8PPNnD8CYPg+tVz0lIwA+0qIAU15errvuukvHjh2T3W7X1VdfrY0bN+rGG2+UJP3+979XeHi4xo8fr5qaGmVlZWnFihWe74+IiNC6des0ffp0ORwOdejQQZMnT9aSJUs8bdLS0pSXl6dZs2bpiSeeUPfu3fXss88qKyvL0CkDMMlkyeiqrtF661c3GukLQHC75H1g/BX7wABtb8EbJfpvQ0+Q5llGACQf7AMDILT1f3iDquvdRvqiZASgpXy/8wyAgFZb71bveXlGwsuoK2yEFwCtwgwMgGZjYzoA/oIAA6BZWGUEQDo9CxuQjxIAEFp4lhGARk09zPHR9fuNPsyxuQgwAM6LkhGARrnr9+lPW0vPed9tyfO+L0MMN/ECaFKfh9YbCy+HlmUTXoAAVlvv1jPvnBtezvTMO6WqNbQysTkIMAC8nKptUO95eUbud7ljeCr3uwBB4PmiQ7rYrwS3dbqdr1BCAuAx6dlteufTr4309ckjY9vlxj4A5n1R8Z3RdiYQYABIktLm5cnUttzMugDBpVfneKPtTODPIyDENZaMTIQXNqYDgtMkR2+Fh124TXjY6Xa+wgwMEMJMloxYZQQEr+jIcE0dldbkKqRGU0el+bRsTIABQhQlIwAt0bhE+ux9YMLD1C77wPA0aiDEnKpt0IAF+Ub6umN4qnJ/MshIXwACQ1vvxMvTqAGcY/J/bdeWg8eN9MUqIyA0RUeGa8qoK9p7GAQYIFRcMT/vovs4NBclIwDtjT+fgCDXuMrIRHhhYzoA/oIZGCCIsTEdgGBFgAGCFKuMAAQz/pwCgozJjekoGQHwV8zAAEGEkhGAUEGAAYIEJSMAoYQ/r4AAd7K63ljJaOKIywkvAAICMzBAABv7+Bbtd5400hclIwCBhAADBKje8/KM9cWsC4BAw59bQIBpLBmZwCojAIGKGRgggIx9fKv2O08Y6YuSEYBARoABAoSpWZcISZ8x6wIgwBFgAD93srpeGYs2Gunrt+MydNuwXkb6AhB6GtyWtpdWqPxEtRI7xWpYWmdFhIe1y1gIMIAfM1ky+mzpTe32iwZA4MsvOabFa/fpWFW1570Ue6wW3pKuMRkpPh8PBXDAT/Wel2ckvETo9CojwguA1sovOabpL+z0Ci+S5Kyq1vQXdiq/5JjPx0SAAfyMyVVGvx2Xwf0uAC5Jg9vS4rX7mtwss/G9xWv3qcFtai/w5qGEBPgRkxvTUTICYML20opzZl7OZEk6VlWt7aUVclzZxWfjIsAAfsLUrEukpE+ZdQFgSPmJ84eX1rQzhQADtDNWGQHwZ107xhhtZwoBBmhHlIwA+L3m3tri21tgCDBAe6FkBCAQfP1tjdF2phBgAB+r+q5O1yx5y0hflIwAtLXETrFG25lCgAF8aGRuob66wN38LUHJCIAvDEvrrBR7rJxV1U1WicIkJdtP78rrS+wDA/hI73l5RsILG9MB8KWI8DAtvCVd0umwcqbGrxfeku7z30kEGKCNsTEdgEA3JiNF912fprCzMkpYmHTf9Wnt8igBSkhAG2KVEYBgkF9yTE9vLT2nhOS2pKe3lmpQz8t8HmJaNAOTm5urH/7wh+rUqZMSExN166236sCBA15tqqurlZOToy5duqhjx44aP368ysrKvNocPnxY2dnZio+PV2JioubMmaP6+nqvNps3b9bgwYMVExOjPn36aPXq1a07Q6CdnH6W0aWHl25xlIwAtJ8LPUqgUXs8SqBFAWbLli3KycnR+++/r4KCAtXV1Wn06NH69ttvPW1mzZqltWvXas2aNdqyZYuOHj2qcePGeY43NDQoOztbtbW1eu+99/Tcc89p9erVWrBggadNaWmpsrOz9aMf/Ui7du3SzJkzde+992rjRjObfQFtqeq7OmMlo48WjNaOhZSMALSfljxKwJfCLMtqdWQ6fvy4EhMTtWXLFl1//fWqqqpSt27d9NJLL+m2226TJH388ccaMGCAioqKNGLECG3YsEE333yzjh49qqSkJEnSqlWrNHfuXB0/flzR0dGaO3eu8vLyVFJS4vlZEyZMUGVlpfLz85s1NpfLJbvdrqqqKtlsttaeItAiI5cV6qtKM6uMDnGvCwA/8Maur/TLl3ddtN0TE67Vj6+9/JJ/XnM/vy/pJt6qqipJUufOp5dOFRcXq66uTpmZmZ42/fv3V8+ePVVUVCRJKioq0sCBAz3hRZKysrLkcrm0d+9eT5sz+2hs09hHU2pqauRyubxegC/1npdnJLw0lowAwB/46z4wrQ4wbrdbM2fO1MiRI5WRkSFJcjqdio6OVkJCglfbpKQkOZ1OT5szw0vj8cZjF2rjcrl06tSpJseTm5sru93uefXo0aO1pwa0CCUjAMGscR+Y892FFyYpJZD2gcnJyVFJSYlefvllk+Nptfnz56uqqsrzOnLkSHsPCSFgZG6hsV11Dy3Llj0+ykhfAGBKUO0DM2PGDK1bt05vv/22unfv7nk/OTlZtbW1qqys9GpfVlam5ORkT5uzVyU1fn2xNjabTXFxcU2OKSYmRjabzesFtJUGt2VsY7q+XaIoGQHwa2MyUrTyzsFKtnuXiZLtsVp552D/3wfGsizdf//9eu2117R582alpaV5HR8yZIiioqJUWFio8ePHS5IOHDigw4cPy+FwSJIcDoceffRRlZeXKzExUZJUUFAgm82m9PR0T5v169d79V1QUODpA2hPfy/+Ug+s+chIXyWLstQxlu2YAPi/MRkpujE9WdtLK1R+olqJnU6Xjdpri4cWrUL6j//4D7300kt644031K9fP8/7drvdMzMyffp0rV+/XqtXr5bNZtP9998vSXrvvfcknV5Gfe211yo1NVXLly+X0+nUpEmTdO+992rp0qWSTi+jzsjIUE5Oju655x5t2rRJv/jFL5SXl6esrKxmjZVVSGgLg5e8pYrv6oz0xawLAJyruZ/fLQowYWfvIfx//vKXv+jnP/+5pNMb2T3wwAP661//qpqaGmVlZWnFihWe8pAkffHFF5o+fbo2b96sDh06aPLkyVq2bJkiI7//S3Tz5s2aNWuW9u3bp+7du+s3v/mN52c0BwEGJjW4LV350PqLN2yGbnHiRl0AOI82CTCBhAADU9Z8cERzXt1tpK+PFozmRl0AuIDmfn5TfAcuIGNBvk7WNhjpi5IRAJjD06iB8+g9L89IeGFjOgAwjxkY4CxV39UZ29uFkhEAtA0CDHCGkbmFRvZ2kZh1AYC2RIABZHaVUd8uUSqYM9pIXwDgTxrclt/sA0OAQcgzucqIjekABKv8kmNavHafjp0xS51ij9XCW9L9fydeINiwyggALi6/5Jimv7BTZ++74qyq1vQXdrbL4wRYhYSQ1PgsIxPhhWcZAQhmDW5Li9fuOye8SPK8t3jtPjW4fbutHDMwCDmUjACg+baXVniVjc5mSTpWVa3tpRVyXNnFZ+PiNy9CCiUjAGiZ8hPNW5nZ3HamUEJCSKitdxsrGY26wkZ4ARAyEjvFGm1nCjMwCHoL3ijRfxd9YaSv/UvGKC46wkhfABAIhqV1Voo9Vs6q6ibvgwmTlGw/vaTal5iBQVDr//AGY+Hl0LJswguAkBMRHqaFt6Q3GV6k0/fALLwl3ef7wRBgEJQaS0bV9e5L7otVRgDgfyghIej85rUSPb/NzKwLq4wAhLrGZdTnE6bTy6hvTE/26SwMv5kRVPo+tF51hvYiYNYFAPx3GTUlJASFxo3pTIQXSkYA8D1/XUbNDAwCHhvTAUDbYRk10AbYmA4A2hbLqAGD2JgOAHyjcRm1dDqsnKnx6/ZYRs0MDAKOyVVGbEwHABc3JiNFK+8crEVv7pPT9f29Lsn2WC28Jd3nT6KWCDAIMKwyAoD25P3717J8+wTqM1FCQkBoLBmZCC+UjACgZfJLjmn6CzvldNV4vV/mqtH0F3Yqv+SYz8fEDAz8HiUjAGg/jRvZNfXnoyU2sgOa1Oeh9aqnZAQA7YaN7IAWOFXboN7z8oyEl+uvtBNeAKCV2MgOaKbJ/7VdWw4eN9IXJSMAuDRsZAc0wxXz82SoYsSsCwAYwEZ2wAU0loxMhBdWGQGAOWxkB5wHJSMA8G+NG9ktXrvP64ZeNrJDyKJkBACBYUxGim5MT9b20gqVn6hWYqfTZSNfz7w0IsCgXdTWu3XVwxuM9DXqCpuev2+Ukb4AAOcXER7m06XSF0KAgc+xMR0A4FIRYOBTbEwHADCBVUjwCZMb090xPJXwAgAhjhkYtLlJz27TO59+baSvTx4Zq+hIcjcAhDoCDNpU2ry8Jjc+ag1mXQAAjfhTFm2isWRkIrxQMgIAnI0ZGBhHyQgA0NYIMDCKkhEAwBf40xZGnKyup2QEAPCZFgeYrVu36pZbblFqaqrCwsL0+uuvex23LEsLFixQSkqK4uLilJmZqYMHD3q1qaio0MSJE2Wz2ZSQkKApU6bo5MmTXm12796tUaNGKTY2Vj169NDy5ctbfnbwibGPb1XGoo1G+vrkkbHK/ckgI30BAIJXiwPMt99+q2uuuUZPPfVUk8eXL1+uJ598UqtWrdK2bdvUoUMHZWVlqbr6+4c/TZw4UXv37lVBQYHWrVunrVu36r777vMcd7lcGj16tHr16qXi4mI99thjWrRokZ5++ulWnCLaUu95edrvPGGkr0PLsrnfBQDQLGGWZbV61j8sLEyvvfaabr31VkmnZ19SU1P1wAMP6Fe/+pUkqaqqSklJSVq9erUmTJig/fv3Kz09XTt27NDQoUMlSfn5+brpppv05ZdfKjU1VStXrtSvf/1rOZ1ORUdHS5LmzZun119/XR9//HGzxuZyuWS321VVVSWbzdbaU8R5nKpt0IAF+Ub6umN4KrMuAABJzf/8NvrnbmlpqZxOpzIzMz3v2e12DR8+XEVFRZKkoqIiJSQkeMKLJGVmZio8PFzbtm3ztLn++us94UWSsrKydODAAX3zzTcmh4xWmPTsNmPhhZIRAKA1jK5CcjqdkqSkpCSv95OSkjzHnE6nEhMTvQcRGanOnTt7tUlLSzunj8Zjl1122Tk/u6amRjU1NZ6vXS7XJZ4NmsIqIwCAPwiaGw5yc3Nlt9s9rx49erT3kIKKyY3pJo64nPACALgkRgNMcnKyJKmsrMzr/bKyMs+x5ORklZeXex2vr69XRUWFV5um+jjzZ5xt/vz5qqqq8ryOHDly6ScESeZLRo/eeq2RvgAAoctogElLS1NycrIKCws977lcLm3btk0Oh0OS5HA4VFlZqeLiYk+bTZs2ye12a/jw4Z42W7duVV1dnadNQUGB+vXr12T5SJJiYmJks9m8Xrh0afPyjOyqGyFWGQEAzGnxp8nJkye1a9cu7dq1S9LpG3d37dqlw4cPKywsTDNnztQjjzyiN998U3v27NFdd92l1NRUz0qlAQMGaMyYMZo6daq2b9+ud999VzNmzNCECROUmpoqSfrZz36m6OhoTZkyRXv37tXf/vY3PfHEE5o9e7axE8eFmdyY7rfjMvQZJSMAgEEtXka9efNm/ehHPzrn/cmTJ2v16tWyLEsLFy7U008/rcrKSl133XVasWKFrrrqKk/biooKzZgxQ2vXrlV4eLjGjx+vJ598Uh07dvS02b17t3JycrRjxw517dpV999/v+bOndvscbKMuvXGPr5F+50nL96wGT5bepMiwsOM9AUACH7N/fy+pH1g/BkBpnV6z8sz0k+ExKwLAKDFmvv5zcMcIel0ycjU4wB+Oy5Dtw3rZaQvAACaQoABJSMAQMAhwIQ4SkYAgEBEgAlRVd/V6Zolbxnpi5IRAMDXCDAhaOSyQn1VWX3xhs1AyQgA0B4IMCGGkhEAIBgQYEIEq4wAAMGEABMCWGUEAAg2BJggZ6pk1CFc2ruUkhEAwD8QYIKUyZLR78YP1Lgf9jTSFwAAJhBgghAlIwBAsCPABBlTJaNucdKOhZSMAAD+iQATJExuTPfRgtGyx0cZ6QsAgLZAgAkCI3ML9VWVmY3pDrG3CwAgABBgAhyrjAAAoYgAE6BMloxYZQQACDQEmABksmTEKiMAQCAiwASQBrelKx9ab6QvVhkBAAIZASZArPngiOa8uttIX6wyAgAEOgJMAMhYkK+TtQ1G+mKVEQAgGIS39wBwYb3n5RkJL93iCC8AgODBDIyfYmM6AADOjwDjh9iYDgCACyPA+BGTq4z6dolSwZzRRvoCAMDfEGD8xN+Lv9QDaz4y0lfJoix1jOX/WgBA8OJTzg8MXvKWKr6rM9IXJSMAQChgFVI7anBb6j0vz0h46dslivACAAgZzMC0E5Mb01EyAgCEGj712gEb0wEAcGkoIflQY8nIRHhJjCe8AABCFzMwPsKzjAAAMIcA4wOUjAAAMIsSUhuqrXcbKxmxyggAgO8xA9NGFrxRov8u+sJIX6wyAgDAG5+KbaD/wxtUXe820hezLgAAnIsSkkGNq4xMhBdKRgAAnB8zMIawMR0AINg1uC1tL61Q+YlqJXaK1bC0zooID2uXsfApaQCrjAAAwS6/5JgWr92nY1XVnvdS7LFaeEu6xmSk+Hw8lJAugclVRqOusBFeAAB+Kb/kmKa/sNMrvEiSs6pa01/YqfySYz4fEzMwrWRyldH+JWMUFx1hpC8AAExqcFtavHafrCaOWZLCJC1eu083pif7tJxEgGkFVhkBAELF9tKKc2ZezmRJOlZVre2lFXJc2cVn46KE1AKNJSMT4YWSEQAgEJSfOH94aU07U/w6wDz11FPq3bu3YmNjNXz4cG3fvr3dxpK7fp+ueniDkb72Lxmj5+8bZaQvAADaUteOMUbbmeK3AeZvf/ubZs+erYULF2rnzp265pprlJWVpfLycp+PJXf9Pv1pa6mRvg4ty+Z+FwBA4Gjq5pdLaWeI3waY3/3ud5o6daruvvtupaena9WqVYqPj9ef//xnn46jtt5tJLxc1TWakhEAIOB8/W2N0Xam+OVNvLW1tSouLtb8+fM974WHhyszM1NFRUVNfk9NTY1qar6/eC6Xy8hYni86dMl9sDEdACBQJXaKNdrOFL+cgfn666/V0NCgpKQkr/eTkpLkdDqb/J7c3FzZ7XbPq0ePHkbG8kXFd5f0/YeWZRNeAAABa1haZ6XYY3W+BdJhOr2h3bC0zr4cln8GmNaYP3++qqqqPK8jR44Y6bdX5/hWfR+rjAAAwSAiPEwLb0mXpHNCTOPXC29J9/kjBfwywHTt2lUREREqKyvzer+srEzJyclNfk9MTIxsNpvXy4RJjt4t/h5WGQEAgsmYjBStvHOwku3eZaJke6xW3jm4XR4l4Je1jejoaA0ZMkSFhYW69dZbJUlut1uFhYWaMWOGb8cSGa7/7/q0Zt/Iy6wLACAYjclI0Y3pyTzM8WJmz56tyZMna+jQoRo2bJgef/xxffvtt7r77rt9Ppb5N52eOrtQiBl1hY1ZFwBAUIsID/PpbrsX4rcB5vbbb9fx48e1YMECOZ1OXXvttcrPzz/nxl5fmX9Tuh4Y3V+5G3frL+985Xk/OyNZv/1/17K3CwAAPhRmWZaPt57xDZfLJbvdrqqqKmP3wwAAgLbV3M9vv7yJFwAA4EIIMAAAIOAQYAAAQMAhwAAAgIBDgAEAAAGHAAMAAAIOAQYAAAQcAgwAAAg4BBgAABBw/PZRApeqcYNhl8vVziMBAADN1fi5fbEHBQRtgDlx4oQkqUePHu08EgAA0FInTpyQ3W4/7/GgfRaS2+3W0aNH1alTJ4WFmXvUt8vlUo8ePXTkyBGesXQWrs35cW2axnU5P67N+XFtmhYs18WyLJ04cUKpqakKDz//nS5BOwMTHh6u7t27t1n/NpstoP+BtCWuzflxbZrGdTk/rs35cW2aFgzX5UIzL424iRcAAAQcAgwAAAg4BJgWiomJ0cKFCxUTE9PeQ/E7XJvz49o0jetyflyb8+PaNC3UrkvQ3sQLAACCFzMwAAAg4BBgAABAwCHAAACAgEOAAQAAAYcA00JPPfWUevfurdjYWA0fPlzbt29v7yEZtXXrVt1yyy1KTU1VWFiYXn/9da/jlmVpwYIFSklJUVxcnDIzM3Xw4EGvNhUVFZo4caJsNpsSEhI0ZcoUnTx50qvN7t27NWrUKMXGxqpHjx5avnx5W5/aJcnNzdUPf/hDderUSYmJibr11lt14MABrzbV1dXKyclRly5d1LFjR40fP15lZWVebQ4fPqzs7GzFx8crMTFRc+bMUX19vVebzZs3a/DgwYqJiVGfPn20evXqtj69S7Jy5UpdffXVns2zHA6HNmzY4DkeqtflbMuWLVNYWJhmzpzpeS9Ur82iRYsUFhbm9erfv7/neKhel0ZfffWV7rzzTnXp0kVxcXEaOHCgPvjgA8/xUP09fA4Lzfbyyy9b0dHR1p///Gdr79691tSpU62EhASrrKysvYdmzPr1661f//rX1v/8z/9YkqzXXnvN6/iyZcssu91uvf7669ZHH31k/fu//7uVlpZmnTp1ytNmzJgx1jXXXGO9//771jvvvGP16dPHuuOOOzzHq6qqrKSkJGvixIlWSUmJ9de//tWKi4uz/vSnP/nqNFssKyvL+stf/mKVlJRYu3btsm666SarZ8+e1smTJz1tpk2bZvXo0cMqLCy0PvjgA2vEiBHWv/zLv3iO19fXWxkZGVZmZqb14YcfWuvXr7e6du1qzZ8/39Pm888/t+Lj463Zs2db+/bts/7whz9YERERVn5+vk/PtyXefPNNKy8vz/rkk0+sAwcOWA899JAVFRVllZSUWJYVutflTNu3b7d69+5tXX311dYvf/lLz/uhem0WLlxo/eAHP7COHTvmeR0/ftxzPFSvi2VZVkVFhdWrVy/r5z//ubVt2zbr888/tzZu3Gh9+umnnjah+nv4bASYFhg2bJiVk5Pj+bqhocFKTU21cnNz23FUbefsAON2u63k5GTrscce87xXWVlpxcTEWH/9618ty7Ksffv2WZKsHTt2eNps2LDBCgsLs7766ivLsixrxYoV1mWXXWbV1NR42sydO9fq169fG5+ROeXl5ZYka8uWLZZlnb4OUVFR1po1azxt9u/fb0myioqKLMs6HQ7Dw8Mtp9PpabNy5UrLZrN5rsWDDz5o/eAHP/D6WbfffruVlZXV1qdk1GWXXWY9++yzXBfLsk6cOGH17dvXKigosP71X//VE2BC+dosXLjQuuaaa5o8FsrXxbJO/y687rrrznuc38Pfo4TUTLW1tSouLlZmZqbnvfDwcGVmZqqoqKgdR+Y7paWlcjqdXtfAbrdr+PDhnmtQVFSkhIQEDR061NMmMzNT4eHh2rZtm6fN9ddfr+joaE+brKwsHThwQN98842PzubSVFVVSZI6d+4sSSouLlZdXZ3Xtenfv7969uzpdW0GDhyopKQkT5usrCy5XC7t3bvX0+bMPhrbBMq/sYaGBr388sv69ttv5XA4uC6ScnJylJ2dfc74Q/3aHDx4UKmpqbriiis0ceJEHT58WBLX5c0339TQoUP105/+VImJiRo0aJCeeeYZz3F+D3+PANNMX3/9tRoaGrz+g5GkpKQkOZ3OdhqVbzWe54WugdPpVGJiotfxyMhIde7c2atNU32c+TP8mdvt1syZMzVy5EhlZGRIOj3u6OhoJSQkeLU9+9pc7LzP18blcunUqVNtcTpG7NmzRx07dlRMTIymTZum1157Tenp6SF/XV5++WXt3LlTubm55xwL5WszfPhwrV69Wvn5+Vq5cqVKS0s1atQonThxIqSviyR9/vnnWrlypfr27auNGzdq+vTp+sUvfqHnnntOEr+HzxS0T6MG2kpOTo5KSkr0j3/8o72H4jf69eunXbt2qaqqSq+++qomT56sLVu2tPew2tWRI0f0y1/+UgUFBYqNjW3v4fiVsWPHev731VdfreHDh6tXr1565ZVXFBcX144ja39ut1tDhw7V0qVLJUmDBg1SSUmJVq1apcmTJ7fz6PwLMzDN1LVrV0VERJxzJ3xZWZmSk5PbaVS+1XieF7oGycnJKi8v9zpeX1+viooKrzZN9XHmz/BXM2bM0Lp16/T222+re/funveTk5NVW1uryspKr/ZnX5uLnff52thsNr/+xR4dHa0+ffpoyJAhys3N1TXXXKMnnngipK9LcXGxysvLNXjwYEVGRioyMlJbtmzRk08+qcjISCUlJYXstTlbQkKCrrrqKn366ach/W9GklJSUpSenu713oABAzwlNn4Pf48A00zR0dEaMmSICgsLPe+53W4VFhbK4XC048h8Jy0tTcnJyV7XwOVyadu2bZ5r4HA4VFlZqeLiYk+bTZs2ye12a/jw4Z42W7duVV1dnadNQUGB+vXrp8suu8xHZ9MylmVpxowZeu2117Rp0yalpaV5HR8yZIiioqK8rs2BAwd0+PBhr2uzZ88er18sBQUFstlsnl9YDofDq4/GNoH2b8ztdqumpiakr8sNN9ygPXv2aNeuXZ7X0KFDNXHiRM//DtVrc7aTJ0/qs88+U0pKSkj/m5GkkSNHnrNFwyeffKJevXpJCu3fw+do77uIA8nLL79sxcTEWKtXr7b27dtn3XfffVZCQoLXnfCB7sSJE9aHH35offjhh5Yk63e/+5314YcfWl988YVlWaeX7yUkJFhvvPGGtXv3buvHP/5xk8v3Bg0aZG3bts36xz/+YfXt29dr+V5lZaWVlJRkTZo0ySopKbFefvllKz4+3q+X702fPt2y2+3W5s2bvZZ+fvfdd54206ZNs3r27Glt2rTJ+uCDDyyHw2E5HA7P8caln6NHj7Z27dpl5efnW926dWty6eecOXOs/fv3W0899ZTfL/2cN2+etWXLFqu0tNTavXu3NW/ePCssLMx66623LMsK3evSlDNXIVlW6F6bBx54wNq8ebNVWlpqvfvuu1ZmZqbVtWtXq7y83LKs0L0ulnV6yX1kZKT16KOPWgcPHrRefPFFKz4+3nrhhRc8bUL19/DZCDAt9Ic//MHq2bOnFR0dbQ0bNsx6//3323tIRr399tuWpHNekydPtizr9BK+3/zmN1ZSUpIVExNj3XDDDdaBAwe8+vjnP/9p3XHHHVbHjh0tm81m3X333daJEye82nz00UfWddddZ8XExFiXX365tWzZMl+dYqs0dU0kWX/5y188bU6dOmX9x3/8h3XZZZdZ8fHx1k9+8hPr2LFjXv0cOnTIGjt2rBUXF2d17drVeuCBB6y6ujqvNm+//bZ17bXXWtHR0dYVV1zh9TP80T333GP16tXLio6Otrp162bdcMMNnvBiWaF7XZpydoAJ1Wtz++23WykpKVZ0dLR1+eWXW7fffrvXPiehel0arV271srIyLBiYmKs/v37W08//bTX8VD9PXy2MMuyrPaZ+wEAAGgd7oEBAAABhwADAAACDgEGAAAEHAIMAAAIOAQYAAAQcAgwAAAg4BBgAABAwCHAAACAgEOAAQAAAYcAAwAAAg4BBgAABBwCDAAACDj/P6LVCshaLRC/AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter([v for v in range(len(parentVTDno))],parentVTDno)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "id": "55d64c64-b473-49d0-b863-d4123cbb9b6c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "for v in range(nVTDs):\n",
    "    if MAP.contains(vtdGeom[v].centroid) and v not in parentVTDno:\n",
    "        print(\"Uhoh,\",v,\"is in the map but not in the parent vtd list\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "ecd50c96-51ce-4d83-b0df-e8c645c35815",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "after above patching, write these contiguous lists to a file, converting to vtd lists\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 if there were NO fragmented VTDs 0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on full or partial VTD master list for unit 0\n",
      "working on full or partial VTD master list for unit 2000\n",
      "working on full or partial VTD master list for unit 4000\n",
      "working on full or partial VTD master list for unit 6000\n",
      "Now converting unit lists to vtd lists for all HDs\n"
     ]
    }
   ],
   "source": [
    "#THIS WORKS FOR BOTH VTD- AND UNIT-BASED (FRAG VTD) -- **NOTE: DOES NOT ADD IN CUT DISTRICTS AND REBALANCE WEIGHTS\n",
    "print(\"after above patching, write these contiguous lists to a file, converting to vtd lists\")\n",
    "noFrag = int(input(\"enter 1 if there were NO fragmented VTDs\"))  #for simple states where units are at least whole vtd's\n",
    "tList = [t for t in range(nHDs)]\n",
    "vtdList = [list() for t in range(nHDs)]\n",
    "unitVTDlist, unitFragVTDlist, unitVTDfrac = [list() for u in range(nUnits)], [list() for u in range(nUnits)], [list() for u in range(nUnits)]\n",
    "unitFullVTDlist, unitPartialVTDlist =       [list() for u in range(nUnits)], [list() for u in range(nUnits)]\n",
    "\n",
    "for u in range(nUnits):\n",
    "    if u %2000 == 0:\n",
    "        print(\"working on full or partial VTD master list for unit\",u)\n",
    "    if allUnits[u] % 1 == 0.5 :\n",
    "        c = int(allUnits[u])\n",
    "        unitVTDlist[u] = countyTractList[c].copy()\n",
    "        unitFullVTDlist[u] = countyTractList[c].copy()\n",
    "    if allUnits[u] % 1 == 0.25 :\n",
    "        CCBnumber = int(allUnits[u])\n",
    "        for c in CCBlist[CCBnumber] :\n",
    "            unitVTDlist[u] += countyTractList[c]\n",
    "            unitFullVTDlist[u] += countyTractList[c]\n",
    "    if allUnits[u] % 1 == 0:\n",
    "        if noFrag == 1:\n",
    "            unitVTDlist[u].append(allUnits[u] )\n",
    "            for i,vv in enumerate(surrounders):\n",
    "                if allUnits[u] == vv:\n",
    "                    unitVTDlist[u].append(surroundedVTDs[i])\n",
    "        else:\n",
    "            unitFragVTDlist[u].append(allUnits[u])\n",
    "            for i,vv in enumerate(surrounders):\n",
    "                if allUnits[u] == vv:\n",
    "                    unitFragVTDlist[u].append(surroundedVTDs[i])\n",
    "            vtdFrac = [0. for V in range(nVTDs)]\n",
    "            for vv in unitFragVTDlist[u]:\n",
    "                V = parentVTDno[vv]\n",
    "                if len(VTDchildren[V]) == 1:  #nonfragmented vtd\n",
    "                    vtdFrac[V] = 1.\n",
    "                else:\n",
    "                    if tractPop[V] > 0:\n",
    "                        vtdFrac[V] += fragVTDgeom[vv].area / vtdGeom[V].area #fragVTDpop[uu] / tractPop[v]  #we overwrote the frag pops earlier; can't use\n",
    "            for v in range(nVTDs):\n",
    "                if vtdFrac[v] > 0.0001:\n",
    "                    if vtdFrac[v] > 0.999:\n",
    "                        unitFullVTDlist[u].append(v)\n",
    "                    else:\n",
    "                        unitPartialVTDlist[u].append(v)\n",
    "                        unitVTDfrac[u].append(vtdFrac[v] )\n",
    "                                    \n",
    "HDpartialVTDlist, HDfullVTDlist, HDvtdFrac = [list() for t in range(nHDs)] ,[list() for t in range(nHDs)],[list() for t in range(nHDs)]               \n",
    "print(\"Now converting unit lists to vtd lists for all HDs\")\n",
    "if noFrag == 1:\n",
    "    for t in popHDlist:\n",
    "        for u in HDunitList[t]:\n",
    "            vtdList[t] += unitVTDlist[u]\n",
    "    outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":vtdList,\"partials\":HDpartialVTDlist,\n",
    "                           \"HDvtdFrac\":HDvtdFrac,\"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "else:\n",
    "    for t in popHDlist:\n",
    "        partialList, partialFrac = list(), list()  #for many HDs, we'll recover whole VTDs when aggregating units\n",
    "        for u in HDunitList[t]:\n",
    "            HDfullVTDlist[t] +=   unitFullVTDlist[u] \n",
    "            partialList +=         unitPartialVTDlist[u]\n",
    "            partialFrac +=          unitVTDfrac[u]\n",
    "        partialSet = set(partialList)  #non-duplicated set of partials across the HD, prepping to aggregate where possible\n",
    "        partialSetFrac, partialSetList = [0. for v in partialSet], list(partialSet)\n",
    "        for i,v in enumerate(partialList):\n",
    "            partialSetFrac[partialSetList.index(v)] += partialFrac[i]\n",
    "        for i,v in enumerate(partialSetList):\n",
    "            if partialSetFrac[i] > 0.999:  #the district has all the fragments of the original VTD contained in the HD's units\n",
    "                HDfullVTDlist[t].append(v)\n",
    "            else:\n",
    "                HDpartialVTDlist[t].append(v)\n",
    "                HDvtdFrac[t].append(      r5(partialSetFrac[i]) )  #save the aggregated fraction of this VTD across all units\n",
    "    outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":HDfullVTDlist,\"partials\":HDpartialVTDlist,\n",
    "                           \"HDvtdFrac\":HDvtdFrac,\"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"patchedVTDs.csv\"   #patchDown, PatchUp, PatchBoth\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "5075814f-4a75-4807-ad8d-b3cc969cb470",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6361 6361 6361 6361 6361 6361\n"
     ]
    }
   ],
   "source": [
    "\n",
    "HDweight = HDweight[0:nHDs]\n",
    "HDvPop = HDvPop[0:nHDs]\n",
    "HDweight = HDweight[0:nHDs]\n",
    "HDfullVTDlist = HDfullVTDlist[0:nHDs]\n",
    "HDpartialVTDlist = HDpartialVTDlist[0:nHDs]\n",
    "HDvtdFrac = HDvtdFrac[0:nHDs]\n",
    "hdCPx, hdCPy = hdCPx[0:nHDs], hdCPy[0:nHDs]\n",
    "print(nHDs,len(tList), len(HDweight), len(HDvPop), len(HDvtdFrac), len(hdCPx) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "e385f357-5b7e-46f5-b054-c5c38d799395",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.0 6361\n"
     ]
    }
   ],
   "source": [
    "print(np.sum(HDweight), nHDs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "id": "8d922813-2854-41d7-9405-22db5d5d5a59",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now append the cut districts and adjust the HDweights\n",
      "13 1 are the number of HD-drawn and cut districts\n"
     ]
    }
   ],
   "source": [
    "print(\"Now append the cut districts and adjust the HDweights\")\n",
    "print(nDistricts,nCutDistricts,\"are the number of HD-drawn and cut districts\")\n",
    "HDweight = [nDistricts/float(nCutDistricts + nDistricts) * HDweight[t] for t in range(nHDs)]\n",
    "tList = [t for t in range(nHDs)]\n",
    "if type(hdCPx) != type(list()):\n",
    "    hdCPx, hdCPy = hdCPx.to_list(), hdCPy.to_list()\n",
    "for L in allCutLists:\n",
    "    tList.append(len(tList))\n",
    "    HDweight.append(1./(nCutDistricts + nDistricts))\n",
    "    pop = np.sum([tractPop[v] for v in L])\n",
    "    HDvPop.append(pop )\n",
    "    HDfullVTDlist.append(L)\n",
    "    HDpartialVTDlist.append(list() )\n",
    "    HDvtdFrac.append(list() )\n",
    "    hdCPx.append(np.sum([tractPop[v]*tractCPx[v] for v in L]) / pop )\n",
    "    hdCPy.append(np.sum([tractPop[v]*tractCPy[v] for v in L]) / pop )\n",
    "    \n",
    "\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":HDfullVTDlist,\"partials\":HDpartialVTDlist,\n",
    "                        \"HDvtdFrac\":HDvtdFrac,\"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"patchedWithCutsVTDs.csv\"   #patchDown, PatchUp, PatchBoth\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "b0b611f7-6c35-495d-b38c-c848317d63ab",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.0\n"
     ]
    }
   ],
   "source": [
    "print(np.sum(HDweight))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "b9d808de-119f-4197-8e0c-8407c105d789",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiwAAAGdCAYAAAAxCSikAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/H5lhTAAAACXBIWXMAAA9hAAAPYQGoP6dpAABtIElEQVR4nO3dd3hUZdrH8e/MpEzapPdegECAhIQWQCwgxYaADTu2ta6ru6uiq7u2RbfZe0F97b2hiIJIb6EFQg0J6T2ZSZt+3j8C0ShgEhKm5P5cVy6ck5OTe46TM795zlNUiqIoCCGEEEI4MbWjCxBCCCGE+D0SWIQQQgjh9CSwCCGEEMLpSWARQgghhNOTwCKEEEIIpyeBRQghhBBOTwKLEEIIIZyeBBYhhBBCOD0PRxfQF+x2OxUVFQQEBKBSqRxdjhBCCCG6QVEUmpubiYmJQa0+fhuKWwSWiooK4uPjHV2GEEIIIXqhtLSUuLi44+7jFoElICAA6HjCOp3OwdUIIYQQojsMBgPx8fGd7+PH4xaB5chtIJ1OJ4FFCCGEcDHd6c4hnW6FEEII4fQksAghhBDC6UlgEUIIIYTTk8AihBBCCKcngUUIIYQQTk8CixBCCCGcngQWIYQQQjg9CSxCCCGEcHoSWIQQQgjh9CSwCCGEEMLpSWARQgghhNOTwCKEEEIIpyeBRQjh8ux2hdKGNsxWu6NLEUL0E7dYrVkIMXCYrDZ2lhvYcqiR7WVNFNa2UlTXgtFiR+upJjMuiDFJIYxOCiY7MRid1tPRJQsh+oBKURTF0UWcKIPBQGBgIHq9Hp1O5+hyhBA9tP5gPZ9tKaep3YwKFWo1qFChUoFa1fFvq8lKUV0rJQ1tWGwKWk81I2IDSYsIIDXcj8RQPw7Vt7KpuIG8Q43UtZhRqWBIZEBngBmdFEJskI+jn64Q4rCevH9LYBFCOIzdrvDnj7bz2dZyUsP9iAv2BUABFEVBUcCuKNgVBR9PDYmhfqSG+5EVH0x6dACemqPf1VYUheL6NjYVN7C5uIHNhxo5WNsKQEygltFJIYxJCiYnMYQhUQFo1KqT9ZSFEL/Qk/dvuSUkhHCIFpOVl34q5LOt5fxr7kguHB2HStU3wUGlUpEc5kdymB8XjY4HoK7FRN6hRjYXN7CpuJFv8iux2hUCvD3ITgxmzOEWmMy4IHy8NH1ShxCi70gLixCi35Q2tLFiXy0NLWbaLFbaTDbazDZqW0ysP1iP2WrnmonJPHDusJNeW7vZxvayps4As+VQI80mKx5qFcNjAzsDzOjEYEL9vU96fUIMBHJLSAjhcGsP1HHpqxsACA/wxtdLg4+nBl8vDYE+nkxMC2N6RhTxIb4OrrSDza6wr7q5M8DkHWqkvKkdgJQwv84+MGOSQkgK9e2z1iAhBjK5JSSEcKj2w60oR/z4l9Pw93buy41GrWJotI6h0TquyE0CoLypvaMPTHEjmw818lFeGYoCYf5e5CQGH+7MG0JGjO6Y/WmEEH3Dua8gQgiXYbXZ+WpHBe9vLGVLSSMWm0KYvxfnZcbi6+mafUJig3yIzYplVlYsAAajhS2HGtlc3Mim4gb+/d1eTNaO4dSj4n/uBzMqIYgAGU4tRJ+SW0JCiF4rb2rny20VbC5uYGtpEw2tZk4ZFMaU9AgmpIUxKMLfrW+dmK12dlXoD49G6miFaWg1o1bB0GgdYw7fQhqTFEyETuvocoVwOtKHRQjRr7aUNPLfpXtZW1iP1kPD6KRgsuKDmJ4RxfDYQEeX5zCKonCwrpXNxQ1sLGpk86EGDtW3AZAQ4svopGDGHr6NlBru59ZhTojukMAihOgX9S0mXlhRyKK1xaRHBXD1hCRmjoh2+v4pjlRjMLL5UGNnK8yuCj12BYJ9PTvngxmTFMLw2EDpByMGHAksQog+V1zXysUvr6PVZOMPk1O48bRUeYPthRaTla0ljWwq7pgTZmtJE+0WG75eGnISgxmfEsr4lBBGxAbh5SHnV7g3CSxCiD6Vd6iB69/KI8jHk/dvGC/9MfqQxWZnZ7me9Qcb2FBUz+biRlpMVrSe6o4AkxzKuJRQMuMD8fZwzc7LQhyLBBYhRJ+x2xUyH1yKyWZnw4IpBPt5Obokt2a12dlVYWBDUT0bDjawsbiBZqMVbw81oxKCGJ8SyrjkUEYlBKF10dFXQhwh87AIIU5Ypb6dn/bWUtHUTrPJynmZMRJWTgIPjZrM+CAy44O4YXIqNrvC7koD6w/Ws6GogUVrinnyh/14adRkxQcxPiWEcSmhZCcEy5ICwq1JC4sQ4jdeXXWQ/y7dh9FqI9zfmxGxgSycM0JuBTkBu11hT1VzlxaYhlYznhoVI+MOB5jkUHISg/GTztDCycktISFEry3fU801b2zmotFx3H/OMJkAzcnZ7Qr7a1o6A8yGonrqWsydayKNSwlhfEoooxOD5f+lcDoSWIQQvfL51nLu/HAbI+KC+OCG8dJHwgUpikJhbcvhTrwNbDhYT02zCbUKhscGHu4D0zEXTKCPBBjhWNKHRQjRKyv21mBXIC7Ih+L6VtKj5AOAq1GpVKRFBJAWEcDl4xNRFIWiutbO8PLltgpeXnkQlQqGRes6A8zY5BCCfKWPknBe0sIihOjU0Grmro+388PuGnJTQnnvhvGOLkn0MUVRKGloY8PBBtYfvo1U3tSOSgVDIgM654EZmxxKiHSyFv1MWliEEL3yfUEVK/fXkRGj4/G5Ix1djugHKpWKxFA/EkP9uGhMPAClDW1sKGpg/cF6lu2p5o21xUBHgMlNDWVCasdcMHILSTiStLAIITBabNz/+U4+yitj3th4/n5uhvRfGcAqmtrZUFTPusJ61hyop7ypHbUKRsQGkpsaxoTUUEYnBePrJZ95xYmRTrdCiG5rNVmZv2gTO8qbeOT8EVyQE+fokoSTKW1oY21hHWsL61lbWE9tswlPjYpR8cGdLTCZ8TKRneg5CSxCiG5RFIWb39nCqv11vHnNGHISQxxdknByR0YhrS2sZ+2BetYdrEffbsFLo2Z4rI7RSSFkJwSTkxhMeIC3o8sVTk4CixDidxXVtfLI1wUs21PDM/NGcW5mjKNLEi7IblcoqDSQd6iRzYcayStuoEJvBCAp1JfsxGBGJ4YwOimYtHB/1GqVgysWzkQCixDiqGx2hdUH6vg4r4wlOyuJCNBy/znDmDE8ytGlCTdS0dRO3qHGzq+CSgM2u4JO60F2YjA5CcFkJwYzMi5QJrMb4CSwCCF+Y+muKv72+U5qmk2kRfhzyZh4Lh+fKP0ORL9rNVnZXtrU2QqzpaSRZqMVlQoGRwSQnRjEqPhgRiUEkSqtMAOKDGsWQnSy2Oy8v7GER7/ZTW5KKC9PHUxmXCAqlbwpiJPDz9uDCWlhTEgLAzpuIx2sa2FLSRNbSxrZWtLE+5tKURQI0HqQFR/EqIRgshOCyIoPkgntBCAtLEK4LUVR+G5XNf9asoei+lbmZsfxyPnDpUVFOKVmo4UdZfrOALOlpJHGNgsAKeF+ZCd0tMCMig9mSFQAGmmFcQvSwiLEAGa3K3y8pYzXVxexp6qZyYPDefbSbIbFSJgXzitA68nEtDAmHm6FURSFQ/VtbC1tZMuhJraWNvLZ1nJsdgVfLw2ZcUGMSggiOyGYrIQgwvxlRJK7kxYWIdxAq8nKjjI9G4rq+XpHJQdqWjhzWCTzJyR1NsML4erazTZ2lDWxtbTjVtKWkiZqm00AJIT4kp3QcStpVEIQQ6N1eGrUDq5Y/B7pdCuEm7PY7Ly+uogfdldzoKals+k8wNuDqcMimTc2gbHJMqeKcG+KolDe1N55C2lrSRO7KvRYbAreHmpGxgV29oUZlRBMpE7r6JLFr0hgEcJNVRuMrNxXy4s/FVJY28rY5BAmDwojKtCH4bE6BkXIvX0xsBktNnZVGDr6wpQ2sfVQY+e8MDGBWkYlBjMqPoicxGAyYgLx8pBWGEeSwCKEi2s329hTZaC0sZ3Shjb07RY2FDWwvbQJlQqGReuYOTyKW05Pk9E+QvyOKr2RbaUdt5C2HGokv1yPyWrHy0PNiNhAchI7WmGyE4KJkFaYk0oCixAuSlEUnl9RyLPLD9BusQGg03oQ5OvF8FgdU9IjOT09ghA/GeYpRG+ZrXYKKg1sOTwnzJZftMLEBft0Li2QnRBMenSA9IXpRxJYhHBBNrvC3Z/s4OO8Mq6blMysrFgSQn3x9/aQ2zxC9LNKfTtbDnX0hdlS0sjO8o6+MD6eGkbGBXaZoVc+MPQdCSxCuJgWk5X5izaSd6iRB8/LIMzfmy+3V7CpuIG6FjPXTUrmb+cMc3SZQgwYHX1h9OQd6hhWnVfS2DkiKTnMr3NIdU5iMIMjpe9Yb8k8LEK4mG0lTWwqbgTg/i92AeChVmG1d3yeOFDb4rDahBiItJ4achJDOlcwVxSFssb2zltIW0qa+GJbBTa7QoC3B1kJHR15cxKDyYoPkjWS+oEEFiEcrNlowa4oDIvWUVBp6NxutSv4e3tw6pBw7j9bWleEcCSVSkV8iC/xIb7MyooFoM3cMf/RkUUeF60p5skf9qNWwZAoHTmJHSFmdGIIccE+0kH+BMktISFOMrPVTl2LieL6Vl5fXcyyPdUoCvh7ezAkKoAonZbYYB8mDwpnbHKIDLsUwkV0rJHUSt6hhs4QU1jbCkB4gDc5h28h5SQFkxGjw9tDlsmQPixCOKm9Vc1c9fpGqgwdIxLSIvy5KjeR8SmhskqtEG6osdXM1tJGNhd3BJjtZU0YLR1DqkceHlKdk9jRmXcgLi8ggUUIJ1RjMHLBi+vw9dLw1+lDCPX3ZmRsoIQUIQYQi83O7kpDR4ApaSSvuLHzA0xSqC/Zh28h5SQGMyjC/T/ESGARwom0mKy8sOIAr68uxtdLw4c35pIa7u/osoQQTqKiqZ3Nhzo68+YdaqSg0tDRmVfrwaiEYEYfboXJjA/C39u9up5KYBHCSejbLZz5v5+oaTZx82mp/GFyKoG+MnpACHFsbWYr20v1XfrCGIxW1CpIj9IxOunnie1cvTOvBBYhHMRktbG1pIm1hfX8tK+W7aVNAJyXGcPT80Y5tjghhEvq6Mzb0tkPJq+kkYOHO/NG6rw7w4srro8kgUWIk8Ris7OjrIl1hfWsLawn71AjJqudIF9PJqSGctqQCHISg0kO9XP7e9FCiJOnodXccQup5HBn3tImTFY73h5qMuOCOmbmPbxGUqgTd+Y9aYHlscceY8GCBdx+++08+eSTALz88su8++67bNmyhebmZhobGwkKCvrdYz333HP8+9//pqqqiszMTJ555hnGjh3brToksIj+ZrcrNButNLaZKWtsZ2eFnnWF9WwqbqDNbMPf24NxySHkpoaSmxrK0CidBBQhxElzZH2kvMN9YTYfaqDa0DEzb0qY3+HOvMGMTgomJcx5OvOelJluN23axEsvvcTIkSO7bG9ra2PGjBnMmDGDBQsWdOtYH3zwAXfeeScvvvgi48aN48knn2T69Ons3buXiIiI3pYoxAkxW+2s2FvD4vxKlu+uodlk7fyej6eG0UnB3HbGIHJTQxkeo8NDFkgTQjiIl4earPggsuKDuHZSMoqiUKE3srn4534wn24pw65AkK9n5y2knMRgMuOC8PFy/jlhetXC0tLSQnZ2Ns8//zyPPPIIWVlZnS0sR6xYsYLTTz+9Wy0s48aNY8yYMTz77LMA2O124uPjue2227jnnnt+tx5pYREnym5X2FraxIaievZXt7C70kBhbQsWm0J6VAAzhkcxODKAIB9PooN8SAjxlbVDhBAupcVkZVtJE3mHW2C2ljTRYrLioVaRERtITkJHC8zoxGAidNqTUlO/t7DccsstnH322UydOpVHHnmkV0UeYTabycvL69Iao1armTp1KuvWrTvqz5hMJkwmU+djg8Fw1P2EOJ6S+jZWHahlbWE96wvrqW81E+DtQWqEP6MSgrl0XAJjk0NIj5IQLIRwff7eHkwaFMakQWFAxwrx+6qb2XyokbziBpYWVPH6miIA4kN8yEnoWBfJz9sDtUrFKYPCTlqQOZoeB5b333+fLVu2sGnTpj4poK6uDpvNRmRkZJftkZGR7Nmz56g/s3DhQh588ME++f1i4PmhoJr/fb+PgkoDGrWKzLhA5o1NYEJaKOOTQ53m3q4QQvQnjVrF0GgdQ6N1XDE+EYBqg7GjBaa4kbxDDXy9o7JzEdYbT03lnpnpDqu3R4GltLSU22+/ne+//x6t1nEpa8GCBdx5552djw0GA/Hx8Q6rR7gOo8XGH9/fSlKoHy9cls0pg8PdbiImIYTorUidlrNGRHPWiGigY5XqXRUGznlmNeNTQhxaW4+u1Hl5edTU1JCdnd25zWazsXLlSp599llMJhMaTc867oSFhaHRaKiuru6yvbq6mqioqKP+jLe3N97ezjtMSzgnRVG49d0tWO0KT1ycxZCoAEeXJIQQTk2lUvHa6iICfTyZkBrm0Fp6FFimTJlCfn5+l23z588nPT2du+++u8dhBcDLy4ucnByWLVvG+eefD3R0ul22bBm33nprj48nxLE0m6ws31NDpE7Lx3mltJhsBPt6csPkFIJ8vRxdnhBCOJ1v8yv5bGs5/70w0+ET0vUosAQEBDB8+PAu2/z8/AgNDe3cXlVVRVVVFQcOHAAgPz+fgIAAEhISCAnpaE6aMmUKs2fP7gwkd955J1dddRWjR49m7NixPPnkk7S2tjJ//vwTfoJCHKHTevKfCzN5eeVBlu2uQeupoaDSgLeHhtunDnJ0eUII4VRqmo3c+1k+0zMimZMd6+hyej8Py7G8+OKLXTrETp48GYBFixZx9dVXA1BYWEhdXV3nPhdffDG1tbU88MADVFVVkZWVxZIlS37TEVeIEzUnO4452XFAx1Dmyf/+kZ0VehRFcen1OIQQoi8pisK9n+ajUav45+wRTnF9lKn5xYD2waYS7v4kn7QIf+47ayinp8tEhUII8eGmUu76ZAcvX5HDtIyj9yftCz15/5apOcWAdvGYBD64YTzRgVrmv7GJ+z/fic3u8hleCCF6rayxjQe/2sWFOXH9GlZ6SsZzigFvXEooY5NDWLSmmIe+LqC0sY3/XZRFiJ90xBVCDDwPfVVAgNaTB84d5uhSupAWFiHoGLp3zaRkXroih+2lTUx7YiX/t66Yxlazo0sTQoiTZsXeGpYWVHPf2UMJ0Ho6upwupA+LEL9SYzDy9y93sbSgGhVw2pBwZmXFMnVopEssECaEEL1R12Li7KdXkRbhz9vXjjspHW1PymrNQrirCJ2WFy7Poa7FxNfbK/h8WwW3vbcVPy8Nf50+hKsnJju6RCGE6FNWm53b3t2KzQ7/uyjLKUYF/ZoEFiGOIczfm6snJnP1xGSK61p5edVB/vFVAeNSQhkaLS15Qgj38d/v97GxuIF3rhtHpAMXODwe6cMiRDckhfnx4HkZaD3VfLerytHlCCFEn1m6q4oXVhRy1/QhjE8JdXQ5xySBRYhu8tSoCfb14vXVRfzf+kM0Gy2OLkkIIU5IUV0rf/5oO9MzIrlhcoqjyzkuCSxC9MBrV41hfEoof/9iJ+P/uYxnlu3HZLU5uiwhhOixHWVNXPTSOsL9vfn3hZlO2W/ll2SUkBC9UKlv5/XVRSxaU0x8iC/XTErm4tHxDl8cTAghumPJzir+9MFWhkbrePmK0YQHeDukjp68f0tgEeIE7K1q5onv97G0oIqcxGDevyEXjdq5P6UIIQYuRVF4ZdVBFn67h7NGRPPfCzPRejpuugaZml+IkyTI15MRcYHYFdhU3EiDTDQnhHBSFpudez/byT+/2cPNp6XyzCWjHBpWekqGNQvRSy+sKOTf3+3By0PN7FGxnJcV47BmVSGEOB6D0cIt72xhXWE9/7pgJBeNjnd0ST0mgUWIo9hf3czTyw+wo6yJVpMNm92O1a5gtyuE+nuTEu7Hir216LQerL7nDHRONoW1EEIcUddi4tJX1lOlN/LWtWOZkBrm6JJ6RQKLEEdx32c72VjcwNUTkgj180KjUeGhVqFWqag2GCmqa2VGRhRXT0ySsCKEcFpGi43r39pMQ6uFT2+eSFqEv6NL6jUJLEIcRXZiMBuLG1icX8mcUbFcMynZaWd/FEKIo7HbFe74YBu7Kw18cEOuS4cVkE63QhzVPTPT+fq2SZw9IpqXVh7klH/9SFFdq6PLEkKIbjFabNz3eT5LdlXx9CWjyIwPcnRJJ0wCixDHMDRax6S0MPy8NKCAjwv1phdCDFx7q5o5/7k1fJJXzmNzRjAtI8rRJfUJuSUkxK+YrDZeXVXEG2uLqW02MTEtlMfnjiQqUG4JCSGcl6IovLG2mIXf7iEp1JfPb5nIsBj3mZtMAosQv/K/7/fx0k8HuWxcAnNz4hgVH+T0U1YLIQa2GoORv3y8g5X7arl6QhL3zEx3qTlWukMCixCHKYrCl9sreGNNMWOTQ3h09ghHlySEEL9r6a4q7vk0H7VKxRvzx3DakAhHl9QvJLCIAauh1cwPBdXsq26muL6N4vpWDtS0MCMjigfOHebo8oQQ4rjazFYe/rqA9zaWMnVoJI/PHUGov/tOXimBRbgFu12hrtWEp1qNj5cGbw/1MW/jmK12nvhhH6+tKsJqt5MQ4ktSmB9jkoJ54JxhTB4cfpKrF0KIntlR1sSf3t9Gpd7IP2ePYN7YeLe/dS2BRbi8lftqufezfMoa2zu3+XhqCA/wJiLAm/AjX/7eqNUqvt5Ryf7qZm49I40rc5MI8fNyYPVCCNF9NrvCiz8V8sT3+xgarWPxHyeREu7a86t0lwQW4dJqmo1c99ZmxiQFc/85w1AUhXaLjfoWM7UtJmqbO76K6lqpbTahAGnh/nx+y0SGxwY6unwhhOi2ssY27vxgO5sONXDTqan8aepgvDwGzuwkEliEy2k329ha0kjeoUa+3VmFh1rF85fmEOgrU+QLIdzT51vLuf/zneh8PHn/+vGMSwl1dEknnQQW4TIqmtpZ+O0efiiopt1iQ6f1YHRSCA/NypCwIoRwW19tr+BPH2xjVlYMD80aTqDPwLzeSWARLuOVVQf5ansFF4+O55pJyQyK8Eetdu9OZkKIgU1RFJ778QCnDg7nqUtGObochxo4N7+Eyzs3M4Ywfy8+2FzKI4sL2FVhcHRJQgjRr1YfqGNPVTN/ODXF0aU4nAQW4TKyE4JZffcZPHFxJlV6I+c+u5q31hU7uiwhhOg3L688yPBYHbkDsM/Kr0lgES5F66lh9qg4pg6LBKDVZHNwRUII0T8KKgys2l/H9aekuP0cK90hfViESymoMPDm2mI+2FzK3Ow4bjot1dElCSFEv3hl1UFig3w4e0S0o0txChJYhMvYcLCeqxZtJNjXiz+fOZirJiY5uiQhhOgX9S0mvtpewT0z0/HQyM0QkMAiXMSuCj1XL9pEdkIwr189xu1WIRVCiF/6cW8tNkVhVlaso0txGhLbhNPTt1m44a080iL8ee0qCStCCPe2s1zPv7/bw5jEEMID3Hcxw56SwCKc3tsbDlHe1M6Cmen4eElYEUK4r6W7qrjwxXVE6rQ8e+nAnnfl1+SWkHB6s7Ji+HBzKfPf2MSUoRFkxATipVFjUxRC/LyYmBZGbJCPo8sUQoheUxSFV1YdZOG3e5iREcX/LsqSD2i/olIURXF0ESfKYDAQGBiIXq9Hp9M5uhzRD9rNNl5ddZBV++vYXWUABVQqMBit+Hpp2HTfVPy8JX8LIVyPxWbn/s938v6mUm4+LZW/TBsyYGbx7sn7t1zhhUvw8dJw25RB3DZlEEaLje2lTazYV8sLKwqJD/bFU3rRCyFckL7Nwk3v5LGpuIF/XzCSC0fHO7okpyWBRbiMFpOVN9YUsWhNMfWtZnRaD26YnMKfpg4aUEusCyHcQ3FdK9e8uYmGVjP/d+04xststsclgUW4hLoWE6f/ZwXNRitXjE/k4jHxpEcFyPwEQgiHajFZsdrsnY+tdoWCCgN5hxppM1uP+XOKAh9vKSPE14vPbp5IcpjfySjXpUlgES7hyR/20Wy0cvn4BB4+f7ijyxFCuBBFUdhS0sjHeWXsqWrG0G4hQOuJzseTAK0HOq0nOq1H5+Mj23y9PDAYLdS3mFGpIMTPC6tNYXelgYJKAwUVBqoMxqP+zmBfT4L9vI5b1/jkUB6bO4Ig3+PvJzpIYBEuYd7YBCqajLy9voQWo5V/zhmBr5e8fIUQx6YoCqv21/HPb3azp6qZ+BAfxiSFEOTjRYvJQrPRSlObmdKGNgztHY8NRgsWW9exKGoVKHS0igBEBHgzNFrH7OxYhkQGoPXs2tKbFuFPari/rP/Tx+SKL1xCRkwgr101mk+3lHPXJzsYEqWTdYSEEMfUarJy0Uvr2FVhYGxyCG9dM5ZJaWG/O/pGURRMVjsGo4U2kw2djyeBPp4ANLWZAQj1l8ncHEECi3AZ7RYbw2J0hPl78emWMgksQohj+ia/kl0VBv529lCumZjc7WHCKpUKraemY0btgK7fk6DiWBJYhEu45o1NLN9T0/k4OyHYgdUIIZxdeVM7ALNHxQ6YOU3cnQQW4RIaDzfFzs2OY8FZ6YT+Tmc2IcTAVt7YTpi/F54y5YHbkP+TwiW8f8N4Lh2XwCdbyrj74x3SmU0IcVw1zSbazDY+31ru6FJEH5HAIlyCt4eGf84ewX1nDWXZnhryDjU6uiQhhBO77+yhtJlt/GvJXtxgBRqBBBbhYuZkx+KpUfHiT4WOLkUI4aS2lDRy8UvrCPP35tlLR0mLrJuQPizCZTQbLUx6/EcsNoVzRkb3+OdtdgWr3Y6XRi0XMCHc2L+W7CEq0Ie3rx0rI3vciAQW4TKa2iy0W2xAx3TYTW3m484QqW+38N3OKn7cW8P20iaqm03Y7AoatapzJstAH08iAryJDtIyJEpHelQAgyMCCPT1PFlPSwjRh3ZXGlh/sIGn542SsOJmVIob3NzryfLUwrVV6Y08vLiAxTsq0ahVDI4MICXcj9ggH7w91Hhq1NjsHVNnr9hbi8VuJzshmDFJIcQF++DjqaHdYuuc0bKpzUyNwURZYzuFtS1Y7R1/DplxgVw9MYmzR8TIwopCuAi7XeGSV9ZTpTey7M+nyiruLqAn798SWIRLqjYY+WF3NTvLDRysbaHKYMRqUzDb7KiAhBBfZgyP4tzMGCJ12m4d02y1U1TXyp4qAx/nlbFqfx3hAd5cMT6RS8clECaf1oRwCuVN7SzdVcW6wno8PdSdawEV1bWytKCad68fx4TUMEeXKbpBAosQfWB/dTOL1hbz6ZYy7ArMzY7lD5NTSZJVVYU46VpNVt5YW8ySnVXkl+vx1KjISQxGo1Z1tJi2W/DQqLnl9FRmj4pzdLmimySwCNGHmtrMvLuxhNdXF1HXYiYrPojJg8K4fnIKAVrp6yLEyXDzO3ks213D1GGRTM+I4vQh4fL35wZ68v4tnW6F+B1Bvl7cfFoa8ycks2RXJT8U1PDKqiL217TwwuU5ji5PCLenKAo/7qnlytxE7jt7mKPLEQ4iPZKE6CYfLw2zR8Xx3GXZ3DVjCD/srsZgtDi6LCHcnkqlYsbwKH7YXSOTwA1gJxRYHnvsMVQqFX/60586txmNRm655RZCQ0Px9/dn7ty5VFdXH/c4V199NSqVqsvXjBkzTqQ0IfrV+JRQLDaFnWV6R5cixIBw1ohoiupa2VDU4OhShIP0+pbQpk2beOmllxg5cmSX7XfccQeLFy/mo48+IjAwkFtvvZU5c+awZs2a4x5vxowZLFq0qPOxt7eMyBDOy2rr+JTn5y13VYXoTxVN7Tz0VQHL9lTjqVF1zsUkBp5eXW1bWlq47LLLeOWVV3jkkUc6t+v1el577TXeffddzjjjDAAWLVrE0KFDWb9+PePHjz/mMb29vYmKiupNOUKcdFGBHUOlqw1GB1cihPsyGC1c/PI6rDaFe88ayqysWEJkpfYBq1e3hG655RbOPvtspk6d2mV7Xl4eFouly/b09HQSEhJYt27dcY+5YsUKIiIiGDJkCDfddBP19fXH3NdkMmEwGLp8CXEyBfl64qFWsbNcbgkJ0V+2HGqktKGdRfPHMH9istOFFZtdob7FxN6qZtYeqOPL7RW8vrqIZ5fvp1n6t/W5HrewvP/++2zZsoVNmzb95ntVVVV4eXkRFBTUZXtkZCRVVVXHPOaMGTOYM2cOycnJFBYWcu+99zJz5kzWrVuHRqP5zf4LFy7kwQcf7GnpQvQZT42aczNjWLKrijunDXF0OUK4Ja1nx/X/+13VpEednCkrjBYb9a1m6ppN1LeaqGs2U3f43/pWE/UtZupaTNS1mGloNWH/VR9gLw81ZqudAK0nV01IOik1DxQ9CiylpaXcfvvtfP/992i13Zs9tDsuueSSzv8eMWIEI0eOJDU1lRUrVjBlypTf7L9gwQLuvPPOzscGg4H4+Pg+q0eI7ogP8WVd4bFbAoUQJ2Z8Sih/PnMw//1+H7urDGTGBTEsRsfQaF23Z55WFAVDu5XaFhP1h4NGRxAxUddq/nnb4X9bTNbfHCPI15Mwf29C/bwI8/cmNdyPUH/vjm3+XoT5ex3+b28aW81M+d9PGE+gr82uCj3vbSzB18uDzLggshKCiAnUDvhFW3sUWPLy8qipqSE7O7tzm81mY+XKlTz77LN89913mM1mmpqaurSyVFdX96h/SkpKCmFhYRw4cOCogcXb21s65QqHstsVKpraaTX/9uImhOg7t56Rho+Xhm93VvHUsv20mTuCQESAd2d4SQzxxWC0UPeL1o+OAGKiodWMxda1GcRToyLUz5uwAC9C/bxJCvVjdGJwZwDpCCMdISTEz6vbaxLlHWrkhrc2Ex2oZVZWbI+ep6IorNhXyysrD7K2sJ7oQC1qlYqXVx4EIMzfm6z4QLLig8iMD2JkXBCBPgNr4rweBZYpU6aQn5/fZdv8+fNJT0/n7rvvJj4+Hk9PT5YtW8bcuXMB2Lt3LyUlJeTm5nb795SVlVFfX090dHRPyhPipLnjw218sa2Cm05LdXQpQrg1lUrFdaekcN0pKdjtCoca2thdaaCgwkBBpYHPtpRTZTASoPXo0goSHx9E2OHg0bU1xBud1qPPWyu+2l7Bnz/aTmZcIC9dMbrb/W2MFhtfbCvn1cOTUWbGBfLMvFHMHB6Fh0ZNTbOR7aV6tpc2sb2siZdWHqTZ2PFB6eoJSdx39tABs8hjjwJLQEAAw4cP77LNz8+P0NDQzu3XXnstd955JyEhIeh0Om677TZyc3O7jBBKT09n4cKFzJ49m5aWFh588EHmzp1LVFQUhYWF3HXXXaSlpTF9+vQ+eIpC9L2yxnZGxAZy94x0R5cixIChVqtIDvMjOcyPs0b8/IHWarPj4cA37e92VXHbe1vRaT2YPzEZ2687thxFY6uZt9cf4s11h6hvNTF1aCSPzh7BmKTgLmEqIkDLmcO0nDksEuho3S2qb+X7gmr+891e9tc089yl2QT5OleH5P7Q55NIPPHEE6jVaubOnYvJZGL69Ok8//zzXfbZu3cven3H6AqNRsOOHTt48803aWpqIiYmhmnTpvHwww/LbR/hlL7aXkHeoUYWzhnh6FKEEODQsAIQH+zL1KGRbCtt4uZ3tgAQpdMyLEZHQogvapWKIxnErigcrG1lQ1E9igIX5MRx7aRkUsL9u/W71GoVqeH+pJ7qT2ZcEDe9k8f5z63h1atGkxYR0F9P0SnI4odC9NCnW8q488PtPDNvFOdmxji6HCGEk1AUhfKmdraVNnXesqpoakdRQDn8fYDEUD/GJIVw0eg4QrvZefhYSurbuO6tTVQ2GXl63ihOT4/og2dy8shqzUL0I0VRuO29rSzfU8P6e6egkxVjhRAO1Gy0cMcH21i2p4YFM9O5/pQUlxlR1JP374HRU0eIPqRSqbj3rKGYrXbe3VDi6HKEEANcgNaTl64YzY2npvLPb/awtOD46/e5KgksQvRCTJAPc7Jjee7HA93qYCeEEP1Jo1Zx94x0YgK1bC1pcnQ5/UICixC9dEFOPM1GK4vWFGG22h1djhBCMCQqgL1V7rlcjSw1K0QvjUkK5qrcRB5ZvJvHl+whIcSX2GBfxiYFMz0jirQI/9+9j2yx2aloasdisxMT5IOvl/xJCiF6b0iUji+3lTu6jH4hV0chekmlUvHgrOFcMjaBTcUNFNW1UlLfxvMrCvnP0n0kh/lxzsho0qN0+HlrqDYYKW8yUtnUTqXeSEOrmQO1LV1aZ6IDtcwYHsXUoZGMjAskQDr0CiF6ID0qgBf1RvTtFrebCVcCixAnaGh0x/TgRxgtNtYV1vP1jkreXFuM4fCslCpVx3Ti0YE+xARpSQj1ZW5OHEMiA/DUqKjQt7O9VM83+ZUsWlMMQHyID0MidUweHMalYxMcPt+EEMK5HahpOfxvMzmJIQ6upm9JYBGij2k9NZyeHsHp6REoykj07RZazTbC/b3x8jh+4Jg9Ko6/nzuMvdXNFFQY2F1pYHdlM//4chfbSpr4z4WZqNWuMVxRCHHy1TabAEgO695EdK5EAosQ/UilUhHk60WQb89+Jj1KR3rUz602X22v4Pb3t9JusfHUJaN+N/gIIQam7MQgPsorxVPjfh9s5KonhAs4NzOGFy/PYdnuGm5+Jw+TtfdL1wsh3FdmfBB2BfZWNTu6lD4ngUUIFzEtI4qXrsxh5f46bn57iwylFkL8RlKoH2oVrNpf5+hS+pwEFiFcyOlDInj5ihxW7a/j71/uxA1W1hBC9CGtp4aMmEAO1rU6upQ+J4FFCBdz2pAIHj4/g/c2lrL+YIOjyxFCOJnwAG/azVZHl9HnJLAI4YIuGh1PUqgvX253zwmihBC9t/5gvVt2zHe/ZyTEAKBSqThtSARfba9kyc4quTUkhAA6VpNvM9twx0uCDGsWwkX9aeogyhrbufHtPFLD/Zg9KpYZw6NIiwhwdGlCCAcxtHfcChoeG+jgSvqeBBYhXFSQrxevXJnD2sJ6Ptxc2rkkQHpUAOdmxnDuyBgSQnswAYwQwuUZjJaOf9stDq6k70lgEcKFqVQqJqaFMTEtDKPFxsp9tXy5vYJnlx/g39/tZWRcIOeMjGZ8SijBvl4E+nri7+Uhs+UK4aa+21UFQLCfl4Mr6XsSWIRwE1pPDdMyopiWEUWb2cryPTV8vb2S/y7dh+kXc7YEeHswPjWUSWlhzBwRRUSA1oFVCyH60tzsOB5ZvJsWo/uNEpLAIoQb8vXy4JyRMZwzMoY2s5WDta00tVnQt1sorG1hzYE6HllcwMNfFzAtI5LLxyWSmxqKSiUtL0K4siO3hH65IKu7kMAihJvz9fL4TQe8P04ZhL7Nwqdby3hnQwmXvrqBlDA/rsxN5NJxiW45JFKIgWBLSSMAk9LCHFxJ35OrkhADVKCvJ/MnJvP9HZP54IbxZMQG8tDXBUx/ciWbimVCOiFc0Xc7qxkU4U+gr6ejS+lzEliEGOBUKhXjUkJ5Zt4ovr19MqF+Xlz6ynre31ji6NKEED2wq0LPkl1VXD85xdGl9AsJLEKITkOiAnjvhvFcPCaeez7N57XVRY4uSQjRTf/+bi+Job7MGRXr6FL6hfRhEUJ04alR8/Cs4fh5e/Dw1wWogGsmJTu6LCHEcSzZWcmKvbU8PW8UHhr3bIuQwCKE+A2VSsU9M9JBgYe+LqCuxcRfpw+RUURCOKHPtpbxl492MCMjirOGRzm6nH4jgUUIcVQqlYoFZw0lPMCbRxbvpqndwj/OzZARREI4kdKGNu76eAfnZ8Xy+NwRbtu6AhJYhBC/47pTUtD5eHLPJzv4oaCaC3LiGJMcQmZcECFuOJumEK7kyR/2E+jjxcPnZ7h1WAEJLEKIbrhodDyj4oN4Y20x724s4fkVhQAkhvqSGRdEZnwQWfGBZMQEovXUOLhaIQaGAzXNfLa1jAfOGYavl/u/nasUN1iX3mAwEBgYiF6vR6dzv9n9hHAmiqJQ0tDGttImtpfq2V7WxM5yPSarHQ+1iiFRAYcDTBCj4oNIi/CXvi9C9INb3t3C1kON/PjX0/D2cM0PCj15/3b/SCaE6FMqlYrEUD8SQ/2YldUxfNJis7O3qvlwiGlic3ED720sQVEgJlDLGUMjmJIeSW5qqLTACNEHmo0WFu+o5MHzMlw2rPSUBBYhxAnz1KgZHhvI8NhALh+fCECLyUreoUZ+3FPDsj3VvL2+BK2nmklpYUzLiOK8zBgJL0L0gqIoLPx2D2oVjEsJcXQ5J43cEhJC9DtFUSisbWHZ7hqW7a5h06EGEkN8eWP+WJLC/BxdnhAuw25XeHLZfp5etp9/zR3JRWPiHV3SCenJ+7cEFiHESXegpoXr39pMbbOJR2cP77y1JIQ4vge+2Mlb6w5x7aRk7j9nmKPLOWE9ef927zFQQginlBbhz5e3TmTq0Ahuf38b/1u619ElCeH0tpc28da6Q1w9IYm/nT3U0eWcdNKHRQjhEAFaT564OItBkQH8+7u9pEb4S0uLEMdR0dQOQKROOyBH3klgEUI4jEql4ubTUtlT1czt72/jmeUHGBkXyIjYQMYlh5IeFYBaPfAuzEIczZ6qZjRqFTPcePr945HAIoRwKJVKxRMXZXJeZgzL99RQUGng6x2VmK12EkJ8ufesoUzPiByQnyiFOOLb/EqeWrafO6YOJnmAdlSXTrdCCKdjtNjYUtLISz8d5Kd9tUxMC+WBczIYEhXg6NKEOOm2lzZx0UvrOHNYJE9fMsqtWh2l060QwqVpPTVMSA3jjfljeP3q0VQ0GZn51Er+K51zxQD06De7SQ335z8XZrpVWOkpCSxCCKelUqk4Iz2S7/40mXMzY3h1VZGjSxLipNpf3czGogZuOi11wE+0KH1YhBBOrd1sY2lBFfnleoJ8PR1djhAn1TsbSgjz92J6xsDsaPtLEliEEA5nsys0tZlRqVR4aFRYrHa2lDTx9Y4Kvi+ops1sY3xKCH+dnu7oUoU4adrMVj7JK+OK3ES8POSGiAQWIcQJMVpstJqs+Gs9ur0IW5vZypoD9awtrGNdYT37a1qw2X/b/39IZAC3nJ7GOSOjSQwdmCMjxMD15bYKWsxW5o1NcHQpTkECixCiV1buq+U/S/eyo0zfuS3Uz4u4YB9ig32IC/YlNsiH2CAf4kJ88PX0YGNxA98XVPHTvlqMFjtxwT6MTwnlsnEJhAdoUanAalNQqWBotG7ADt8Uwmy189a6Q5w2OJz4EF9Hl+MUJLAIIXrs9dVFPPR1AeNTQnh87giCfL0wtFuo1Bspa2yjvKmdgooqypvasdi6tpxkxQfxp6mDmZ4RJYFEiKOw2RUue3U9BZUG/nbOOEeX4zQksAghemRdYT0PfV3ADZNTWDAz/bgTutntCrUtJsoa22k1WRkarSM8wPskViuE67HZlc7bqw99VcDNp6dx9ohoNAN4SDPIxHFCiG5qaDWzan8tC7/ZQ2ywDx/9IXdAzwkhRH9oN9v4ekcFCSG+7Ktu5o21xRTWtpIU6stNp6Uye1ScW3XA7cn7t7SwCCGOymixsWRnFSv31bK1tImiulYAThkUxr8vGNgTWAnRX+74YBtLdlX9ZntxfRt3f5LPB5tK+fTmiQ6ozPEksAghfqOiqZ1r39zM7koDw2N1TB4Uxp+mDiI7IVg6AArRT77bVcWSXVU8PncE2QnBtJistJpstJqttJmttJhsxAX5OLpMh5HAIsQA1WqyUljb0vFV00pxfSulje2UN7ZR12ImSqflmz+ewrAYuc0qRH9rM1t54IudTEmP4KLR8bLY51FIYBHCTdjsChVN7VQbjDS0mumY1kRBUUAB6lpMFNa0UFjbSmFtC5V6Y+fPRum0JIX5MjjCnzOGRBAf4sOU9EgCZWZZIU6KT7eUU9ts4u/nZkhYOQYJLEK4KH2bhbySBrYcamJLSSPbS5toNduOub+nRkVSqB+p4f7MyY4lNdyf1HB/UsL9CNBKMBHCURRF4a11xUwdGklCqNxyPRYJLEK4iKY2MxuKGthwsIH1B+vZXWVAUTomaxuVEMwtZ6SRERNIdKCWED8vNCoVRz6oqVDh563BQ+M+owuEcBebihvZV93CA+dkOLoUpyaBRQgnZbMrbDhYz0/7all9oI6Cyo6AEhvUMTvs/IlJjE0OISHEV5qQhXBhr6w6SEqYHxNSQx1dilOTwCKEkzlU38oneWV8sqWc8qZ2IgK8mZgWxtUTkhifEiqjdIRwI7srDXxfUM1/LpSpAn6PBBYhnECLyco3+ZV8nFfGxqIG/L09OGdkNBeOjic7IUhaUIRwU8+vKCQu2IdZWTGOLsXpSWARwkFMVhs/7a3lm/xKlhZU026xMSktjKcuyWLasCh8vLq38rEQwjUV1bWyeEcFD84ajqf0L/tdJ3SGHnvsMVQqFX/60586txmNRm655RZCQ0Px9/dn7ty5VFdXH/c4iqLwwAMPEB0djY+PD1OnTmX//v0nUpoQTsdktXGwtoVlu6tZ8OkOxjzyAzf8Xx67K5u56dRUVt99Bv937ThmZcVKWBFiAFi0pogQPy8uzIlzdCkuodctLJs2beKll15i5MiRXbbfcccdLF68mI8++ojAwEBuvfVW5syZw5o1a455rH/96188/fTTvPnmmyQnJ3P//fczffp0CgoK0Gq1vS1RCIdoaDVTUGFgT5WBfdXNHKpvo7ShjUqDkSMrd8UF+3BlbhKzsmIYFBng2IKFECddtcHIB5tKuem0VLSe8gGlO3oVWFpaWrjssst45ZVXeOSRRzq36/V6XnvtNd59913OOOMMABYtWsTQoUNZv34948eP/82xFEXhySef5G9/+xuzZs0C4K233iIyMpLPP/+cSy65pDclCnFStR7ug/LZ1nLWHaxHUcDbQ83gyACSwvwYk9Qxmic+xJeEUF9iArXSL0WIAez5Hw+g9dRwzaRkR5fiMnoVWG655RbOPvtspk6d2iWw5OXlYbFYmDp1aue29PR0EhISWLdu3VEDS1FREVVVVV1+JjAwkHHjxrFu3bqjBhaTyYTJZOp8bDAYevM0hOgTm4ob+NP726jQt5ObEspjc0YwJimExFC/Ab8cvBDityqa2nlvYym3Tx2ETiZt7LYeB5b333+fLVu2sGnTpt98r6qqCi8vL4KCgrpsj4yMpKrqt6tPHvmZI/t092cWLlzIgw8+2NPShehz20ubuOTl9WTFB/HOdeNICvNzdElCCCf38sqD+HpruGpCkqNLcSk96nRbWlrK7bffzjvvvOPQviULFixAr9d3fpWWljqsFjEwGYwWXl11kHmvrGdQhL+EFSFEt+jbLHywqZQrc5Pw95aBuj3Ro7OVl5dHTU0N2dnZndtsNhsrV67k2Wef5bvvvsNsNtPU1NSllaW6upqoqKijHvPI9urqaqKjo7v8TFZW1lF/xtvbG29v756ULkSvWWx26lvM7KtuZleFgZ3len7cW4PJauei0fHcd/ZQ6TQnhOiWdzYewqYoXDE+0dGluJweBZYpU6aQn5/fZdv8+fNJT0/n7rvvJj4+Hk9PT5YtW8bcuXMB2Lt3LyUlJeTm5h71mMnJyURFRbFs2bLOgGIwGNiwYQM33XRTL56SED1ntNjYXWlgZ4WB3ZUGKpraqdIbqTYYaWyzdO7n7+3BsGgdN56aysVj4onUySg2IUT3mK123lxbzOysWMID5EN3T/UosAQEBDB8+PAu2/z8/AgNDe3cfu2113LnnXcSEhKCTqfjtttuIzc3t0uH2/T0dBYuXMjs2bM753F55JFHGDRoUOew5piYGM4///wTf4ZCHIXNrrC1pJGV++tYvb+W7WV6bHYFD7WKtAh/4kN8GZscQqROS7i/N6H+XqSE+5MY4ivTZwshemVNYR3VBpP0XemlPr+B9sQTT6BWq5k7dy4mk4np06fz/PPPd9ln79696PX6zsd33XUXra2t3HDDDTQ1NTFp0iSWLFkic7CIPtdutvH08v18tLmUuhYzQb6eTEgNZfaoWEbGBTEkKkBu7wgh+sVPe2uJC/ZhaLTMvdQbKkU5MpWV6zIYDAQGBqLX69HpdI4uRzix+Ys2srawnsvHJ3LWiCiy4oNl6LEQ4qSY+dQqhkYF8L+LsxxditPoyfu3dFEWA0ZRXSs/7q3lqUuymJUV6+hyhBADSG2zid2VBs4cGuHoUlyWrLYkBoyShjYAchKDHVyJEGKgeeKHfQAE+3k5uBLXJYFFDBiBPh0zSlYbTL+zpxBC9J2Ww0t3zBubwPyJMhV/b0lgEQNGelQACSG+3PtpPs1Gy+//gBBC9IH3NpTQYrRy6xlpji7FpUlgEQOG1lPDa1eNpkLfzlWvb8Riszu6JCGEm7Pa7CxaU8R5WTHEBvk4uhyXJoFFDCiDIgP44xmD2FLSRFFdq6PLEUK4uR92V1OhN3KN3Ao6YRJYxIBistp49JvdAMQH+zq4GiGEu1t9oI6UcD+GxwY6uhSXJ4FFDBilDW3MX9Sxyvj1pyTj4yUTxAkh+te6wnrGJYc4ugy3IPOwCJekKApNbRZazVYsNgWrzY7Jasdis2O22rHYFCw2O+0WG9UGI3mHGvl2ZxVBPp58+IdcxsoFRAjRz2oMRgprW7l96mBHl+IWJLAIl3GovpVPtpTz075adlcYMHez06yXh5rkUD8eOGcYF46Ow9dLXvZCiP637mA9ALkpoQ6uxD3IlVs4rSMLFP6wu4Zlu6vZX9OCv7cHp6dHMCszhuhALf5aDzw1ajw1Krw0Gjw9VHhp1Hhq1Hh7qPH20KDz8UClkun3hRAn1497akgJ95OVmfuIBBbhNBRFobypnW2lTSzfXcOPe2tobLMQ4ufF6UMiuPPMwUweHI6ft7xshRDOb/OhRs4cFunoMtyGXPnFSdVstFClN1JlMFKlN1JtMFKpN7K/poU9lQYMRivQMcnbpeMSmDI0ksy4IFmgUAjhUgxGC+VN7QyNlgV5+4oEFtFFs9HC/poWShvaOFTfRkOrGZPVjsliw2i1YbUpeHqoD992UeGpUeN1+LECmK12rHY7FmtHp1ezzU5Dq5kqg5FqvZFWs63L7wvx8yJSpyUl3I9TB6cyNDqAjJhAInVax5wAIYToA2sP1KEo0n+lL0lgGeCMFhsbihrYVNTAmsI6dpTpsdkVAEL9vAj190LrqcHbQ43WU4NGraLNbMN8eDTOkXBittlRqcBTrcbTQ4WHuiPEeGhUBPt5MTRaR5ROS2Sglihdx1eEzhutpwwtFkK4n4/zysiI0REfIvM99RUJLAOQ3a6wqbiBz7aWszi/kmajlWBfTyakhnFBThxZ8UEkhPgSoPV0dKlCCOGSDta1curgcEeX4VYksAwQiqKwq8LAN/mVfLm9grLGduKCfbh6QhLnZsaQFu6PWvqJCCHECas2GDlY28rtUwY5uhS3IoHFjSmKQn65nm/yq/h2ZyWH6tsI8vVkRkYUc7LjGJ0YLCFFCCH62J6qZgBGxQc7uBL3IoHFzdjsCtvLmliys4pv8ispa2wnxM+L6RmRPDxrOLmpoXhqZEUGIYToL5uKGgjx8yIuWFZn7ksSWFycoigcqGlhzYE61hTWs/5gPc1GK2H+XkzPiOKsEdGMSw7BQ0KKEEKcFGsK68hNDZUW7D4mgcXFLVpTzENfF3Q+/uMZaUweHM6ohGCZu0QIIU6yZqOFHWV6LsyJd3QpbkcCiwuqbTaxq0LPrgoDP+2r7fK9kXFBjE6Shf2EEMIRVu+vw2ZXmJAq86/0NQksLqC4rpVPtpSxpaSRPZXN1LeaAfD39mBYtI75E5PIiAkkPSqAjBiZVVEIIRxl+Z4aYgK1JIbK/Ct9TQKLk1IUhTfXFvPF9gq2ljQRoPVgQmool49PZGh0AOlROhJCfOUeqRBCOAmjxcaSnVVcOSFRFlztBxJYnIyiKBTXt/HFtnKe/GE/AE9enMWM4VEyK6wQQjixj/LKaDFbmZMd5+hS3JIEFieyq0LPvZ/ms71Mj1oFpwwK44XLc/CX1YmFEMKpGYwW7v98JwCxQTKcuT/IO6ETufuTHeypbOblK3IYnxqKTqbGF0IIl7D38GRxANe/tZn/u3acA6txTxJYnMQneWXsLDewcM4IpmVEObocIYQQ3XCwtoU31xbzUV4ZgyL8GZ0UwsQ0GSHUHySwOIHPt5az4LN8LsyJ45IxMnZfCCGcndFi49HFu3lnwyFC/b25fHwit52RJovG9iMJLA52xWsbWLW/jtmjYnn4/OHSs1wIIZxcRVM7N76dx56qZu47exiXjUuQQREngQQWB2o2Wli1v464YB/+d1GmhBUhhHByRXWtXPbKelQqFZ/eNIHhsYGOLmnAkMDiAEaLDZPVzsaiBgBunzJIwooQQji5AzXNzHtlAzqtB+9cN56oQK2jSxpQJLCcRO1mG7e9t5XVB2oxWe2dw5WHyey0Qgjh1Erq27js1Q2E+HrxzvXjCPP3dnRJA44ElpPEYrNz9tOrOFjXykWj4xgZF0R5Uzs5CcFkxEiTohBCOKtKfTuXvroeXy8P3r5OwoqjSGDpR/uqm3l3Qwn7a5rZWW6g1WTllStHc+awSEeXJoQQohsKKgzc+HYeigLvXDeO8AAJK44igaWf1LeYmPbESgBmZERx1YQkzhwayYg4aU0RQghX8EleGfd+lk9ahD8vXp5DjMxg61ASWPqJTVEAuGFyCveeNdTB1QghhOgug9HCo1/v5oPNpVyYE8fD5w+XYctOQAJLP/kkrxyAs0dEO7gSIYQQ3bV8TzX3fbaTZqOVf80dyYWj42QUp5OQwNIP9lc388qqg4xNCmGk3AISQgin12qycv8XO/l0SzmnDArjsbkjZRFDJyOBpQ/trjTw3I8H+HZnFclhfrx4RY4kcyGEcHLbSpv484fbqNQb+e+FmczJjpVrtxOSwNIH9O0WJv/rR/TtFhJCfLn/7KFcMlamahZCCGdmMFr415I9vLOhhIwYHV/dNonUcH9HlyWOQQJLL+UdamRzcQM7yvUs2VmFza4wONKfxX88BU+N2tHlCSGEOI5v8yt56OsCDO0W/n7OMK7ITUKjllYVZyaBpQfazTZ2Veh5bXUR3+6swtdLQ3pUANdNSuby8YnEh/g6ukQhhBDHoW+38MAXO/liWwVT0iN46Pzh0lfFRUhg6QabXeHJH/bxyqqDGC12onRanrw4i/MyY1BLIhdCCJewsaiBOz7YhqHdwlOXZDErK9bRJYkekMDSDR9uLuWZ5Qe45fRUZg6PZnBkAF4ecttHCCFcgcVm5+ll+3nuxwPkJAbz/g3jpUXcBUlg6YbShjYCvD24fcpgCSpCCOFCiutauf2Dbews13PH1MHcfHqa9FVxUfLu2w1njYim2WTl/U0lji5FCCFEN32xrZyzn15FU5uZj2/M5bYpgySsuDBpYemGjBgdOq0HD3yxiyidlilDI+VFL4QQTkrfZuEfX+3is63lnJ8VwyOzR+DvLW93rk6lKIcXvXFhBoOBwMBA9Ho9Op2uX37HjrImLn5pPe0WG2H+XsweFUt2QjCTB4fjJ38IQgjhFH7cU8M9n+6gzWzjH+dmyCRwTq4n798SWHrAZLWxvVTPN/mVLM6vpLbZRJCvJ2cMieDG01IZHBnQb79bCCHEsdnsCo8u3s3ra4qYPDicx+eOIDpQhis7OwksJ8nB2hY+yivj863lVOqNBGg9iNRpyU4I4oKceMYmh5y0WoQQYqAqbWjjzx9uZ/OhBh44ZxhXTUiSVhUXIYHlJDNabHxfUE15UztVeiPL9lRT2tDOC5dlM1NWaxZCiH7z1fYK7v00H52PJ/+9KJPxKaGOLkn0QE/ev6XzRR/Qemo4NzOm8/ED5wzjlH/9yOZDjRJYhBCiH7SZrfzjy118uLmMczNjeOT84QT6eDq6LNGPJLD0Mbtd4cGvdlHe1E5ymJ+jyxFCCLezq0LPbe9upcpg5N8XjOSCnDi5BTQASGDpI3a7wtKCKp5ZfoCCSgP/nD2CS8clOLosIYRwG3mHGvlgUwmfbilnSFQAX982iRRZXXnAkMBygux2ha92VPDs8gPsr2lhQmoo718/nnFyH1UIIfrEofpW/vHlLn7cW0uUTstdM4ZwZW4SWk+No0sTJ5EElhP05A/7eHr5Afy9PfjkplxyEmVkkBBC9AW7XeGtdcU8vmQvof5ePDNvFGePiJZFZwcoCSwnaExyCB5qFS0mK9tK9RJYhBDiBFltdhbnV/L8j4XsrW7mqtxE7pqRLpN0DnA9WkvohRdeYOTIkeh0OnQ6Hbm5uXz77bed3y8sLGT27NmEh4ej0+m46KKLqK6uPu4x//GPf6BSqbp8paen9+7ZOMApg8LZ98hMwvy9Ka5rdXQ5Qgjh0vIONTLzqVXc/v42VCp4/rJsHpw1XMKK6FkLS1xcHI899hiDBg1CURTefPNNZs2axdatW0lKSmLatGlkZmayfPlyAO6//37OPfdc1q9fj1p97GyUkZHBDz/88HNRHq71wmw2WalrMSGd1IUQondaTVb+s3Qvb6wtZmRcEF/fNonhsYGOLks4kR4lg3PPPbfL40cffZQXXniB9evXU15eTnFxMVu3bu2c/OXNN98kODiY5cuXM3Xq1GMX4eFBVFRUL8p3Dh9uKgXgbJlzRQghsNkV9lQZiNRp8fPyoKDSwLbSJgCOfK5TqTr+WwGqDSa+2l5BfauJ+84ayvyJybLArPiNXjdl2Gw2PvroI1pbW8nNzaWwsBCVSoW3t3fnPlqtFrVazerVq48bWPbv309MTAxarZbc3FwWLlxIQsKxhwSbTCZMJlPnY4PB0Nun0SfKm9rx1KhIjz75s+wKIYSzef7HA/z3+32/2e5zeFSPgsIv51gP9vVifEoIf5o6mCSZv0ocQ48DS35+Prm5uRiNRvz9/fnss88YNmwY4eHh+Pn5cffdd/PPf/4TRVG45557sNlsVFZWHvN448aN44033mDIkCFUVlby4IMPcsopp7Bz504CAo6+mODChQt58MEHe1p6r20paeSFFYUYLTZMVjsmqx2z1Y7ZasNgtFLb3BGenl9xgAUzh560uoQQwhlde0oy9a1m1hyoY39NCwDxIT68cuVo0qPkg53onR6vJWQ2mykpKUGv1/Pxxx/z6quv8tNPPzFs2DCWLl3KTTfdRFFREWq1mnnz5lFQUMDYsWN54YUXunX8pqYmEhMT+d///se111571H2O1sISHx/fL2sJNbWZmf7kSvy8PRgapcPLQ42XRt3xr4candaTEH8vQv28mDw4HH/pGCaEEF2U1Lfxh7fzKK5r5bG5I5iVFevokoST6Ne1hLy8vEhLSwMgJyeHTZs28dRTT/HSSy8xbdo0CgsLqaurw8PDg6CgIKKiokhJSen28YOCghg8eDAHDhw45j7e3t5dbj31p+d+PECb2cbnt0yUpcqFEKIXEkJ9+fSmCdz7WT63v7+NHWV67pmZjqemRwNVxQB3ws0Bdru9S2sHQFhYGADLly+npqaG8847r9vHa2lpobCwkCuuuOJES+sT3h4avD00ROm0ji5FCCFclo+Xhv9dlElWfBAPf13A1zsqqDaYuH3KIO44c7CjyxMuoEfxdsGCBaxcuZLi4mLy8/NZsGABK1as4LLLLgNg0aJFrF+/nsLCQt5++20uvPBC7rjjDoYMGdJ5jClTpvDss892Pv7LX/7CTz/9RHFxMWvXrmX27NloNBrmzZvXR0/xxOQkBlPXYqK0od3RpQghhEtTqVRcNSGJD2/Mpd1sA8DLQ1pZRPf0qIWlpqaGK6+8ksrKSgIDAxk5ciTfffcdZ555JgB79+5lwYIFNDQ0kJSUxH333ccdd9zR5RhHbhkdUVZWxrx586ivryc8PJxJkyaxfv16wsPD++DpnbhRCUEAbCpuICHU17HFCCGEG9hT2YzBaOXqCUncfFqqo8sRLqLHnW6dUU867fTGGf9dwcHaVu6Zmc68MQkE+nr2+e8QQgh312a28o8vd/Hh5jKuzE3kwfMyUMmMmwNaT96/JbB0w4GaFl76qZAvtlXgoVFxQU4c8ycmkyzzBQghxG9sL21iX3UzQGcgMVpsvLa6iCq9kYdmZXBBTpyEFSGBpb/UNpt4e/0h3l5/iIY2M1PSI7l2UjLjU0LkD08IMeBZbHY+3FzKA1/swmb/7VvLxLRQHjxvOGkR/g6oTjgjCSz9zGix8cW2cl5bXcS+6hYyYnRcMzGZczKj8fbQ9PvvF0IIZ2K02Hh3Qwkv/FRIbbOJi0bH8fD5w1Ef/iB35F1GOtiKX5PAcpIoisKq/XW8vqaIFXtrCQ/w5orxiVw2LoFQ/5MzT4wQQjiKxWbno81lPLN8PzXNJuaMiuW6U1IYEnX0WcqF+DUJLA5woKaZRWuK+WRLGXYFZmfFcs2kZPnDFUK4HYvNzlfbK3h62X4ONbRx7sgY/jR1ECnhcqtH9IwEFgdqbDXz3qYS3lp7iCqDkUlpYVw7KZlTB4ejltVHhRAuzGS18emWcp5fcYDShnampEfw1xlDZH0g0WsSWJyAxWbnm/xKXl9dxPYyPSnhfsyfmMzc7Fh8vWS9ISGE66hpNvJJXjmL1hRR22Ji5vAobjk9jYyYQEeXJlycBBYnoigKW0oaeW11EUt2VhGg9WTe2ASuzE0kJkjWJhJCOCez1c4Pu6v5YFMpqw/UoVGpmD0qlusnJ5MWIbe6Rd+QwOKkyhrbeHNtMe9vLKXNYuO8zBgWzEwnQtYpEkI4iQM1LXy4uZRP8sqobzWTnRDE3Jw4zh4RTZCvl6PLE25GAouTazFZ+XhzKc8sP4DZZmfBzKFcMia+131c2s02nvhhH4t3VFLe1E5mfBAf/mG8DLEWQnSLvs3C4vxKPtlSRt6hRoJ8PZkzKo5LxsYzOFJaU0T/kcDiIprazCz8Zg8fbC5lcKQ/F49JYPaoWEL8fv9TTLPRwoq9tSwtqGbFnhqaTVa8NGrMNnvnPkvvmCwXGyHEcT2+ZA+vrS7CarMzaVA4F42O48xhkfKBR5wUElhczKbiBhatKeL7gmoApg2L4qIx8UxKC0Pzi1aXaoOR7wuqWVpQzbrCOiw2hYwYHWcOi2TOqDgSQn1RFIXXVhfxyOLdXD0hiX+cl+GopyWEcHJ2u0LKvd8QG+TDZzdPkNvT4qTryfu3DFdxAmOSQhiTFEJ9i4nPtpbz4eZSrnp9IzGBWi7IicPbU8PSgmq2lzahUasYnxLCfWcNZeqwSOKCu64grVKpuO6UFH7YXc2Hm0vRqFWMSQohKlBLiK8X8SE+soyAEAOYoihUGYzsLDfwysqDAMzNiZOwIpyetLA4IUVR2FbaxIebS/lqeyWKonDqkHCmDYvi9CER3Votutlo4ckf9vNNfiWVemPndh9PDacMCuOR84cTodOys1yPod1Cu8VGi8kKQKROy/DYQPy9Jc8K4arsdoW8kkaK61ppaDVT3tTOvupm9lW30NBqBiA13I+Hzx/OhNQwB1crBiq5JeRGTFYbQK/vJyuKQk2zifoWM9XNRr7Nr+TDzWUA/PnMwfz3+33H/Fl/bw9evDyHiWmh0iojhAtQFIVdFQa+3F7Bl9sqqDJ0fFgJ0HoQpdMyODKAtAh/MmJ0ZMQGEhOolb9t4VASWMRxfZtfyU3vbOl8PD4lhKcvGYWftwcKUNHUzoebSnl1dREAj80ZwSVjExxUrRDiePRtFtYW1vHTvlp+2ldLpd5IiJ8X54yMZlZWDCNig2TRQeG0JLCI32W02NhQ1EConxfDY48+W6XdrnDus6vZVWHg3evHSbOxECeRxWZnW2kTK/fVsrm4kTOHRXL1hCRqmk1sLG5gU1EDm4ob2FvdjKJ03N6ZPDicM9IjGJ8SiqdGQopwfhJYRJ9pbDVzxn9XYFc6hklHSsc8IfpNaUMbP+2rZeW+WtYV1tNsshLk60lGjI41B+oJ9vWksc0CQEqYX0eH/eQQxqeE/KYDvhCuQAKL6FMVTe2c9+wavDQqPvhDLvEhcmEUoq/948tdvLG2GI1aRXZCEJMHhTN5cDjDYwPRqFWsPVDHyv11ZMYFMjophPAAb0eXLMQJk2HNok/FBPnw9W2TuPjldcx9YS03nprKRWPif3cUUbPRQm2ziZggH7SeMgmVEMczLKbjYm1XFK6dlMKM4VFdvj8hLYwJaXJbVgxc0sIiuq1Kb+Sf3+zm252VqFQqRsUHcdNpqZw6OLxzpMGaA3VsLGpg86EG1hXWY1dArYKEEF+CfL1IDffn1jPSSA7zc/CzEeLkstjsrNpfy8HaVsL8f24dKW9qZ/GOSgoqDfh5aZiWEcWdZw6WlkwxIMgtIdGvKpra+WJbBU8t24fRYic5zI8z0iNoaDXz2dZyAEbEBjI3O5bkcH/KG9s5WNuCwWjpHFL993OHcfWEJBlSKdxetcHICysK+Wp7BfWH5z/5Ja2nminpkZybGc1pQyKkNVIMKBJYxEmhKArrDtbzxdYKPthcCoBGraLgoenHnDdmb1Uzz/14gC+3V3BlbiIPzRp+MksW4qQ6WNvCH9/fSnFdG5eMiWd2dixDIgOw2n++7HqoVXjIiB4xQElgESddu9lGSUMbaRH+XdY/OpaHvy7gtdVFfHJTLjmJISehQiH6n92ucLCuhR1len7aV8s3+ZVE6rQ8e2k2WfFBji5PCKcjgUU4vR1lTZz37BpUqo61lDJidIyIDWRkXCDJYd0LPUI4g/3VzSzbU8OaA3VsK2mi+fASF6nhfswbm8Dl4xPlNo8QxyCBRbiEPVUGluysYn9NC7vK9RTXtwHg66VheEwg2YnBjEsOIdjPi9RwPwK0v7+GkhAng77Nwpc7Kvhocyk7yvT4eGoYl9KxiGlWfBDDYwMJ9JHXqxC/RwKLcEn6dgu7yvXkl+vZUaZnY3EDtc0moKNj4tShkdwzM10myBIOYbMrrDlQx0d5ZXy3qwqbXeH0IeFckBPPaUPCpRVFiF6QwCLcgqIolDa0YzBa+GlfLf/+bi8AW+8/k1azFS8PNeH+3jLSSPSrZqOF9zaW8Na6Q5Q1tpMW4c+FOXHMzo4lIkBmfhbiREhgEW7p2/xK/vj+Viy2ri/Z7IQgFs4ZyZCoAAdVJtxRs9HCm2uLeWVVEe1mG+eMjOby3ERGxQdJSBaij0hgEW6rptnI4h2VJIT4YrHZefKH/eypakal6lhV+uIxsqq0ODHtZhuvrT7YEVQsNi4dm8CNp6YSFSitKUL0NZmaX7itiAAt8ycmdz6eMTwai83OP77cxd2f5JMS7s+YJBkmLXpOURS+3lHJwm92U9di5tJxElSEcCYyW5FweZ4aNQ/PGo6fl4a/fLQdN2g0FCfZgZpm5r2yntve20pGbCBL75jMP87LkLAihBORFhbhFtRqFaelR7B4RyXZD3/P1gem9ejn7XaF8qZ21hyow65AbLAPwb6eBPl4ERfsg8Vup0pvpK7FTJXeSLXBSKW+nWqDCY8jc8aoIDpQy+biRsoa24kJ0hIX7MuUoRFMHRopo0icUKvJynM/HuCVVQeJDfLhrWvGMnlwuKPLEkIchQQW4TYyYnQs3lGJr1f3X9Ymq417P93JJ1vKjrmPr5cGk9WO7RfTqXt5qIkJ1BKp02JXFFQqFRuLGgDIjAvknMxoqvVGdpbrO9dXWnvPGcQE+fTy2Ym+tq+6mbnPr8Vks3PL6WnceGqqhEohnJgEFuE23l53CIDYIB92lusZHht43P2b2szMeX4tB+taGZ0YzE2npZIRE0iovxdVeiP6dgt1LSb2VTfj5+1BUqgfYf7eROq8CfTx/M1IEUVRaDPb8PP26LJtyv9+4mBtK59tLeeW09P6/omLHrHbFdYU1vHfpftoNllZ9udTSQ33d3RZQojfIaOEhNsormvluR8P8FFeR2tJSpgfz12WTVKoHz5eP39yVhSF5XtquPbNzQD858JMLsiJ65ea9lQZmPHkKgDign3w8/LA21ONp0ZNgNaDtHB/VCqwK2BXFJTD/9oVBU+NmkAfT3RaT3Q+nof/24NQf2/ign2kNaCHjBYbn20t55VVBzlY20pKuB/XTkrmsnGJji5NiAFLhjWLAc1ktfHGmmL+/d3ezlVx0yL8ufHUVEL9vJj/xiag47bOs/NGMS0jqt9qURSFpQXV7Chrwmy1Y7EpGC02PtxcSkq4PxabHY1ahVqlQqNSoVKBWqVCrQaz1Y6+3YKh3Uq7xfabY8cG+TA40p9hh9dhyogJJC7YR+YI+RWLzc57G0t4etkB6ltNTBsWyXWnpDA6MVjOlRAOJoFFCDo6VK4/WM/OcgMbiupZW1gPdPQx+dPUwZw2JNxl3rDMVjsGowV9u4Uag4nSxjYO1rayt8rArgoDNYeXMAjy9WR4TCDDYwMJ8vWkrtmEn7cH/t4epEb4MTY5FH/vgXMneHtpE3d/soO91c3MGRXHLaenkiK3f4RwGhJYhDiK1fvraDZamJ4RhdrNVoOuMRjZWaFnZ7mB/HI9O8v11DSbiAv2wWSx02y00Gq2EaD1YOGcEZw9ItplwlpvWGx2nlm2n+dWFDI0OoCFs0cyIu74fZqEECefBBYhBMrh0UtH/ru4vo3/fLeXxfmVpEX48/xl2QyOdL/lDOpbTNzwf3lsK23itjPSuOX0NDw1MuWUEM5IAosQ4qgUReG11UU8sng3AC9ensOM4f3Xh+dkW76nmvs+24nFZuflK0eTnRDs6JKEEMfRk/dv+dghxACiUqm47pQUdj80A4B1hXUOrqhvNBst3PnBNq55YzODIgP48tZJElaEcDMDp/edEKLTnioDALsrmx1cyYnbW9XMdW9toqnVwn8vzGROdqxb988RYqCSwCLEAPT2+hLUKnhwVoajSzkhG4sauPbNTcQF+/LOteNJCPV1dElCiH4igUWIAeZgbQufbCnjrBFRDI123T5f3+2q4rb3tjI6MZiXrsghQOvp6JKEEP1IAosQA8yROVsmpbnmIn8Wm52/fbaTD/NKOWtENP+7KBNvD5n1Vwh3J4FFiAFmf00LAFOHRTi4kt75Jr+SDzaXAnDLaWl4qmXsgBADgfylCzGAlNS38fi3e5gzKpaIAK2jy+mVM4dFcurgjtahs55excgHlzq4IiHEySCBRYgBot1s49b3thDs5+nSnW1VqDh9SDhh/t4A/GFyioMrEkKcDHJLSIgBQN9u4eZ38thf3cK7149zyQ6q+jYLb60rZtHaYvTtFs4dGc2Np6WSHuW6HYeFEN0ngUUIN7e70sCNb+fR2Gpm0fwxjHKxCdVqDEZeXV3EO+sPYbErXDQ6jhtOSZUhzEIMMBJYhHBjn20tY8Gn+SSH+fPWNWNJDPVzdEndVtrQxvMrCvkkrwxvDzVXTkjimonJhAd4O7o0IYQDSGARwg2ZrXYeWVzAW+sOMTc7jkfOH46Pl2sM/TVabDz/4wFeXHkQndaD26cO4orcRHQueBtLCNF3JLAI4WYq9e3c/M4WdpUbeHT2cC4dm+AyU9WvPVDHgs/yqWwycsPkFG4+PRVfL7lMCSEksAjhVtYeqOO297bi7aHmwxtzyYoPcnRJ3dLUZuaf3+zmw81ljE0O4fWrx5Aa7u/osoQQTkQCixBuQFEUXlp5kH8t2cOE1DCeuiSLUH/n7+uhKAqL8yv5x5e7MFntLJwzgotHx6NWu0aLkBDi5JHAIoSLMxgt/PWj7Xy3q5pbTk/lzjOHoHGBN/zdlQYeX7KHFXtrmZERxYOzMojUueZkdkKI/ieBRQgXVtrQxlWLNlJrMPHyFTlMy4hydEm/y2ZXeGNtMY99u5vYIB9evDyHGcOdv24hhGP1aKbbF154gZEjR6LT6dDpdOTm5vLtt992fr+wsJDZs2cTHh6OTqfjoosuorq6+neP+9xzz5GUlIRWq2XcuHFs3Lix589EiAFmZ7me2c+vxW5X+PK2SS4RVnaW65nz/BoeWVzAZeMSWXrHqRJWhBDd0qPAEhcXx2OPPUZeXh6bN2/mjDPOYNasWezatYvW1lamTZuGSqVi+fLlrFmzBrPZzLnnnovdbj/mMT/44APuvPNO/v73v7NlyxYyMzOZPn06NTU1J/zkhHBXm4sbuOTl9cQGafn4pgkkhznv/Cp7q5p58KtdzH5+Dec8s5o2s42Pb8zlH+dl4OUhq4MIIbpHpSiKciIHCAkJ4d///jfx8fHMnDmTxsZGdLqOqbL1ej3BwcEsXbqUqVOnHvXnx40bx5gxY3j22WcBsNvtxMfHc9ttt3HPPfd0qwaDwUBgYCB6vb7zdwvhrgoqDFz88joyYnS8dtUY/Lyd987u66uLeOjrAgDOGRnNmcMiOWtENJ4aCSpCiJ69f/f6qmGz2Xj//fdpbW0lNzcXk8mESqXC2/vnkQlarRa1Ws3q1auPegyz2UxeXl6XMKNWq5k6dSrr1q3rbWlCuC19m4Xr39pMYqgvr1w52qnDCkBKeEfLT2KoLw+cM4xZWbESVoQQvdLjK0d+fj7+/v54e3tz44038tlnnzFs2DDGjx+Pn58fd999N21tbbS2tvKXv/wFm81GZWXlUY9VV1eHzWYjMjKyy/bIyEiqqqqOWYPJZMJgMHT5EmIg+NsXO2k2WnjpitEusYDh4MgApqRHcKi+jdfWFDm6HCGEC+txYBkyZAjbtm1jw4YN3HTTTVx11VUUFBQQHh7ORx99xFdffYW/vz+BgYE0NTWRnZ2NWt23n6gWLlxIYGBg51d8fHyfHl8IZ7S2sI6vtlfw4KwMYoN8HF3OMVltdlbtr+Xmd/I45V8/srG4gT+cmsJNp6Y6ujQhhAvrcXuyl5cXaWlpAOTk5LBp0yaeeuopXnrpJaZNm0ZhYSF1dXV4eHgQFBREVFQUKSkpRz1WWFgYGo3mNyOJqquriYo69siBBQsWcOedd3Y+NhgMElqE27v0lQ0AzMqMdXAlv2Wx2VlXWM+3Oyv5blc1Da1mUsP9uP/soVwwOh5/J791JYRwfid8FbHb7ZhMpi7bwsLCAFi+fDk1NTWcd955R/1ZLy8vcnJyWLZsGeeff37n8ZYtW8att956zN/p7e3dpa+MEO6utKENgIdmZTjNLLBmq501hXV8m1/J0oJqmtosJIT4ctHoeM4eEc3wWJ3LrGEkhHB+PQosCxYsYObMmSQkJNDc3My7777LihUr+O677wBYtGgRQ4cOJTw8nHXr1nH77bdzxx13MGTIkM5jTJkyhdmzZ3cGkjvvvJOrrrqK0aNHM3bsWJ588klaW1uZP39+Hz5NIVzbf5buxVOj4sIcx7Ykmq0dt3u+ya/i+4IqDEYryWF+XDYugZnDo8mIkZAihOgfPQosNTU1XHnllVRWVhIYGMjIkSP57rvvOPPMMwHYu3cvCxYsoKGhgaSkJO677z7uuOOOLsc4csvoiIsvvpja2loeeOABqqqqyMrKYsmSJb/piCvEQLa2sB4/bw98vDQO+f1ljW28t7GEDzaVUtfScbvn6glJzBwRTXpUgIQUIUS/O+F5WJyBzMMi3NmnW8q488Pt/HP2CC4dl3DSfq+iKKzaX8db64pZvqcGPy8P5mTHMm9cAulR8ncmhDhxPXn/lp5wQjixfdXN3PtZPhfkxDFvbN/fDmo1WVm1vxYfLw/azTbGJocQ5OPJ97ureXb5AfLL9QyN1vHI+SOYlRXj9PO+CCHcl1x9hHBiV7++EaPFzkOzMvrktou+3ULeoQbWH2xg/cF6dpTpu3w/wNuDZpMVgHHJIbxz3TgmpIbKLR8hhMNJYBHCiQ2KDKBCb+ScZ1aTEuZPgNYDT40Ko8WOyWrDalPw13qQFu7PoMgANGoVKkABmtrMNLSaqTaYOFDbwv7qZir1RgCidFrGp4QwNzuO+lYzM4dHEaD14OWVB3lr3SEAnrl0FBEBWsc9eSGE+AXpwyKEk9tY1MBHm0tpaDXTbLJittrReqrRemrwUKswGK0UVBhoOdwy8ks+nhoidN4MighgcKQ/gyMDyIoPIjHU95itJs1GCxq1Cl8v+TwjhOhf0odFCDcyNjmEsckhx93HbLXTYrKiKAp2Bax2O8G+Xmg9ez6qyBWm/BdCDDwSWIRwA14eakI8vBxdhhBC9BtZNlUIIYQQTk8CixBCCCGcngQWIYQQQjg9CSxCCCGEcHoSWIQQQgjh9CSwCCGEEMLpSWARQgghhNOTwCKEEEIIpyeBRQghhBBOTwKLEEIIIZyeBBYhhBBCOD0JLEIIIYRwehJYhBBCCOH03GK1ZkVRADAYDA6uRAghhBDddeR9+8j7+PG4RWBpbm4GID4+3sGVCCGEEKKnmpubCQwMPO4+KqU7scbJ2e12KioqCAgIQKVSObqc3zAYDMTHx1NaWopOp3N0OQ4n5+Nnci66kvPxMzkXXcn5+Jk7nQtFUWhubiYmJga1+vi9VNyihUWtVhMXF+foMn6XTqdz+RdXX5Lz8TM5F13J+fiZnIuu5Hz8zF3Oxe+1rBwhnW6FEEII4fQksAghhBDC6UlgOQm8vb35+9//jre3t6NLcQpyPn4m56IrOR8/k3PRlZyPnw3Uc+EWnW6FEEII4d6khUUIIYQQTk8CixBCCCGcngQWIYQQQjg9CSxCCCGEcHoSWHpoxYoVqFSqo35t2rQJgOLi4qN+f/369cc99tF+5v333//N78/Ozsbb25u0tDTeeOON/nqq3dJf52P79u3MmzeP+Ph4fHx8GDp0KE899VS3fndVVVW/Pudj6c/XRklJCWeffTa+vr5ERETw17/+FavV+pvf72qvjV86cOAAAQEBBAUFHfe4b7zxxjGPW1NTc9zf7cyvjV/q7rkA971u/FJ3z4e7Xjd+qSevDVe8bhyXInrEZDIplZWVXb6uu+46JTk5WbHb7YqiKEpRUZECKD/88EOX/cxm83GPDSiLFi3q8jPt7e2d3z948KDi6+ur3HnnnUpBQYHyzDPPKBqNRlmyZEm/Pufj6a/z8dprryl//OMflRUrViiFhYXK//3f/yk+Pj7KM88807nPjz/+qADK3r17uxzXZrP1+/M+mv46F1arVRk+fLgydepUZevWrco333yjhIWFKQsWLOjcx1VfG0eYzWZl9OjRysyZM5XAwMDjHretre03x50+fbpy6qmndu7jiq+NI3pyLhTFfa8bR/TkfLjrdeOInpwLV71uHI8ElhNkNpuV8PBw5aGHHurcduRNaevWrT06FqB89tlnx/z+XXfdpWRkZHTZdvHFFyvTp0/v0e/pT315Pn7t5ptvVk4//fTOx0cuPI2NjSd03P7SV+fim2++UdRqtVJVVdW57YUXXlB0Op1iMpkURXHd18YRd911l3L55ZcrixYt6tab9C/V1NQonp6eyltvvdW5zRVfG0f09Fy463XjiBN5bSiKe1w3jujJuXCX68YvyS2hE/Tll19SX1/P/Pnzf/O98847j4iICCZNmsSXX37ZrePdcssthIWFMXbsWF5//fUuS26vW7eOqVOndtl/+vTprFu37sSeRB/q6/PxS3q9npCQkN9sz8rKIjo6mjPPPJM1a9b0qu7+0FfnYt26dYwYMYLIyMjObdOnT8dgMLBr167OfVz1tbF8+XI++ugjnnvuuV4d96233sLX15cLLrjgN99ztddGb8+Fu143TvS1Ae5z3ejpuXCX68YvucXih4702muvMX369C6LL/r7+/Pf//6XiRMnolar+eSTTzj//PP5/PPPOe+88455rIceeogzzjgDX19fli5dys0330xLSwt//OMfAaiqqury4gOIjIzEYDDQ3t6Oj49P/zzJHujL8/FLa9eu5YMPPmDx4sWd26Kjo3nxxRcZPXo0JpOJV199ldNOO40NGzaQnZ3d58+tp/rqXBzr//uR7x1vH2d/bdTX13P11Vfz9ttv93oRt9dee41LL720y3N0xddGb8+Fu143+uK14S7Xjd6cC3e5bnTh6CYeZ3H33XcrwHG/du/e3eVnSktLFbVarXz88ce/e/wrrrhCmTRpUo9quv/++5W4uLjOx4MGDVL++c9/dtln8eLFCqC0tbX16Ni/x5nOR35+vhIWFqY8/PDDv7vv5MmTlcsvv7xbx+0uR5+L66+/Xpk2bVqXba2trQqgfPPNN4qiuO5rY/bs2crdd9/d+binzf5r165VAGXz5s2/u6+zvzZO9Fwc4S7XjRM9H+503ejNuXC260ZfkBaWw/785z9z9dVXH3eflJSULo8XLVpEaGhot1oJxo0bx/fff9+jmsaNG8fDDz+MyWTC29ubqKgoqquru+xTXV2NTqfr8yTsLOejoKCAKVOmcMMNN/C3v/3td/cfO3Ysq1ev/t39esLR5yIqKoqNGzd22XbkdRAVFdX5ryu+NpYvX86XX37Jf/7zHwAURcFut+Ph4cHLL7/MNddcc9zf8+qrr5KVlUVOTs7v1u3sr40TPRdHuMt140TOh7tdN3pzLpztutEXJLAcFh4eTnh4eLf3VxSFRYsWceWVV+Lp6fm7+2/bto3o6Oge1bRt2zaCg4M7F7jKzc3lm2++6bLP999/T25ubo+O2x3OcD527drFGWecwVVXXcWjjz7arTp6c55/j6PPRW5uLo8++ig1NTVEREQAHf/fdTodw4YN69zHFV8b69atw2azdT7+4osvePzxx1m7di2xsbHHPW5LSwsffvghCxcu7FYdzv7aOJFz8Uvuct3o7flwx+tGb86Fs103+oSDWnZc3g8//HDUJj1FUZQ33nhDeffdd5Xdu3cru3fvVh599FFFrVYrr7/+euc+n376qTJkyJDOx19++aXyyiuvKPn5+cr+/fuV559/XvH19VUeeOCBzn2ODEH761//quzevVt57rnnnGYIWl+fj/z8fCU8PFy5/PLLuwz3q6mp6dzniSeeUD7//HNl//79Sn5+vnL77bcrarVa+eGHH/r3yf6Ovj4XR4YnTps2Tdm2bZuyZMkSJTw8/KjDE13ttfFrR2vq/vX5OOLVV19VtFrtUUd7uOJr49e6cy7c+brxa905H+563fi17pwLV79uHI0Ell6aN2+eMmHChKN+74033lCGDh2q+Pr6KjqdThk7dqzy0Ucfddln0aJFyi/z4rfffqtkZWUp/v7+ip+fn5KZmam8+OKLv5kb4Mcff1SysrIULy8vJSUlRVm0aFGfP7fe6Ovz8fe///2o93wTExM793n88ceV1NRURavVKiEhIcppp52mLF++vF+eX0/09blQFEUpLi5WZs6cqfj4+ChhYWHKn//8Z8VisXTZxxVfG792tAvx0c6HoihKbm6ucumllx71OK742vi17pwLd75u/Fp3zoe7Xjd+rbt/J6583TgalaL8YvybEEIIIYQTknlYhBBCCOH0JLAIIYQQwulJYBFCCCGE05PAIoQQQginJ4FFCCGEEE5PAosQQgghnJ4EFiGEEEI4PQksQgghhHB6EliEEEII4fQksAghhBDC6UlgEUIIIYTTk8AihBBCCKf3/6R1XbF2epBbAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vtdUSE = [0. for v in range(nVTDs)]\n",
    "for u in range(nUnits):\n",
    "    for v in unitFullVTDlist[u]:\n",
    "        vtdUSE[v] += 1\n",
    "    for i,v in enumerate(unitPartialVTDlist[u]):\n",
    "        vtdUSE[v] += unitVTDfrac[u][i]\n",
    "\n",
    "plt.scatter([v for v in range(nVTDs)], vtdUSE)\n",
    "plt.show()\n",
    "unused = list()\n",
    "for v in range(nVTDs):\n",
    "    if vtdUSE[v] < 0.2 and MAP.contains(vtdGeom[v].centroid) and tractPop[v] > 0:\n",
    "        unused.append(v)\n",
    "        #print(v,\"in county\",countyNo[v],\"has pop\",tractPop[v],\"and map-total usage of\",vtdUSE[v],\"its surroundedness is\",v in surroundedVTDs)\n",
    "        plotPoly(vtdGeom[v].centroid.buffer(0.1))\n",
    "        plotCenter(v,vtdGeom[v],8)\n",
    "    #if vtdUSE[v] > 0.2 and vtdUSE[v] < 0.95:\n",
    "    #    plotCenter(r3(vtdUSE[v]),vtdGeom[v])\n",
    "plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "3d2a393c-5ab8-4140-80eb-1153c2ef41f9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for u in range(nUnits):\n",
    "    if unitUse[u]  < 0.9:\n",
    "        plotPoly(unitGeom[u],0.2)\n",
    "        plotCenter(r3(unitUse[u]),unitGeom[u],6)\n",
    "    if  unitUse[u]  > 1.1:\n",
    "        plotPoly(unitGeom[u],1.2)\n",
    "        plotCenter(r3(unitUse[u]),unitGeom[u],6)\n",
    "plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "404935e6-f0de-4b51-9db9-020aa208f852",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "integrity check: vtd-based pops\n",
      "x = n surrounded, y= unit - vtd-based\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"integrity check: vtd-based pops\")\n",
    "HDvtdbasedPop = [0. for t in range(nHDs)]\n",
    "HDvPop = [0. for t in range(nHDs)]\n",
    "nSurrs = [0. for t in range(nHDs)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "        if u in surroundedVTDs:\n",
    "            nSurrs[t] += 1\n",
    "    for v in HDfullVTDlist[t]:\n",
    "        HDvtdbasedPop[t] += origVTDpop[v] #tractPop[v]\n",
    "    for i,v in enumerate(HDpartialVTDlist[t]):\n",
    "        HDvtdbasedPop[t] += HDvtdFrac[t][i] * origVTDpop[v] #tractPop[v] also works\n",
    "        \n",
    "plt.scatter([nSurrs[t] for t in popHDlist], [HDvPop[t] - HDvtdbasedPop[t] for t in popHDlist] )\n",
    "print(\"x = n surrounded, y= unit - vtd-based\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ef27af54-daf5-4e8f-9230-bce5b0b1e705",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "3ad3342b-b8e3-46f5-a3e5-f49df386b88f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, read in the votes by vtd to compute ensemble vote margin vs. true state vote margin\n",
      "Let's read in the 2020 and 2016 voting data for NJ\n",
      "In year/election 2020 Dem and GOP total votes were 2607921 1882732 for a stateGOP of 0.41926\n",
      "There are a total of 6361  vote-mapped voting districts from election(s) in year  2020\n",
      "In year/election 2016 Dem and GOP total votes were 2148267 1601915 for a stateGOP of 0.42716\n",
      "There are a total of 6361  vote-mapped voting districts from election(s) in year  2016\n"
     ]
    }
   ],
   "source": [
    "print(\"Now, read in the votes by vtd to compute ensemble vote margin vs. true state vote margin\")\n",
    "#note: we started w possibility of separate election --> 2020 vtd files by year.  Now we use ALARM combined 2016+2020 --> 2020 csv's for all exc CA\n",
    "# copied from \"HDpartisanAnalysis\"\n",
    "print(\"Let's read in the 2020 and 2016 voting data for\",STATE)\n",
    "#DemCandidates, RepCandidates, vestDFs = [\"G16PREDCLI\"], [\"G16PRERTRU\" ], list()\n",
    "#DemCandidates, RepCandidates, vestDFs = [\"G20PREDBID\", \"G16PREDCli\"], [\"G20PRERTRU\" ,\"G16PRERTru\" ], list()\n",
    "DemCandidates, RepCandidates, vestDFs = [\"pre_20_dem_bid\", \"pre_16_dem_cli\"], [\"pre_20_rep_tru\" ,\"pre_16_rep_tru\" ], list()\n",
    "nYears = 2\n",
    "unitIDs, vestReps,vestDems,yearLean = [list()]*nYears, [0]*nYears, [0]*nYears, [0.5]*nYears\n",
    "years = [str(2020),str(2016)]\n",
    "DemVotes, RepVotes = [list() for y in years], [list() for y in years]\n",
    "vestDir = \"./state_map_files/\" + STATE.lower()\n",
    "vestDF = pd.read_csv(vestDir + \"_2020_vtd.csv\")\n",
    "mergedDF = vestDF.copy() #pd.merge(mergedDF,vestDF, on = \"GEOID20\")\n",
    "for y,year in enumerate(years):\n",
    "    DemVotes[y], RepVotes[y], unitIDs[y] = mergedDF[DemCandidates[y]], mergedDF[RepCandidates[y]], vestDF[(\"GEOID20\")]\n",
    "    vestDems[y], vestReps[y] = np.sum(DemVotes[y]), np.sum(RepVotes[y])\n",
    "    yearLean[y] = vestReps[y]/float(vestDems[y]+vestReps[y])\n",
    "    print(\"In year/election\",year,\"Dem and GOP total votes were\",int(vestDems[y]),int(vestReps[y]),\"for a stateGOP of\",r5(yearLean[y]) )\n",
    "    nVTDs = len(DemVotes[y])\n",
    "    print(\"There are a total of\",nVTDs,\" vote-mapped voting districts from election(s) in year \",years[y])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f628069d-4177-401e-bf49-b7f194d0ef8b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "id": "5cf73783-4a48-4a3f-a2e3-c1b9ff32c859",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now let's read in our ensemble of HD districts for NJ\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the filename with the vtd assignments to districts; e.g. NC2666patchedWithCutsVTDs NJ6361patchedVTDs.csv\n",
      "enter the number of HD-drawn districts in the state; e.g. 8 12\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This ensemble or enacted map describes 6361 drawn districts.  This state has 12 districts per map\n",
      "converting vtd list strings to vtd lists by drawn district ...\n",
      "the total weight across all rows should be 1.000, actually is 1.0\n",
      "I am assuming we already read in a 'tractPopFile' of Census vtd geoms & pops with a GEOID20 column\n",
      "translating from HD order of precinct rows to VEST order\n"
     ]
    }
   ],
   "source": [
    "print(\"Now let's read in our ensemble of HD districts for\",STATE)\n",
    "infilename = input(\"enter the filename with the vtd assignments to districts; e.g. NC2666patchedWithCutsVTDs.csv\")\n",
    "\n",
    "HDdf = pd.read_csv(\"2024state_HD_output/\"+infilename)\n",
    "nRows = len(HDdf)\n",
    "nStateDistricts = int(input(\"enter the number of HD-drawn districts in the state; e.g. 8\"))\n",
    "print(\"This ensemble or enacted map describes\",nRows,\"drawn districts.  This state has\",nStateDistricts,\"districts per map\")\n",
    "\n",
    "HDvPop = HDdf[\"HDvPop\"].to_list()\n",
    "HDweight = HDdf['HDweight'].to_list()\n",
    "#tractPop = HDdf['tractPop'].to_list()\n",
    "#statePop = np.sum(tractPop)\n",
    "tractCPx = HDdf['centroid x'].to_list()\n",
    "tractCPy = HDdf['centroid y'].to_list()\n",
    "HDvtdListString = HDdf[\"HDvtdList\"]\n",
    "print(\"converting vtd list strings to vtd lists by drawn district ...\")\n",
    "HDvtdList = [list() for t in range(nRows) ]\n",
    "for t in range(nRows):\n",
    "    if HDvtdListString[t] != \"[]\":\n",
    "        HDvtdList[t] = ast.literal_eval(HDvtdListString[t])\n",
    "\n",
    "if \"partials\" in HDdf.columns.values: #\"splitTractNo\" #.to_list():\n",
    "    splitTractList, splitTractUseList = HDdf['partials'], HDdf['HDvtdFrac']\n",
    "    splitTractNo = [ast.literal_eval(splitTractList[t])    for t in range(nRows)]\n",
    "    splitTractUse = [ast.literal_eval(splitTractUseList[t]) for t in range(nRows)]\n",
    "else :  #incoming file didn't use any partial units, only whole ones\n",
    "    splitTractNo, splitTractUse = [[] for t in range(nRows)] , [ [] for t in range(nRows)]\n",
    "\n",
    "print(\"the total weight across all rows should be 1.000, actually is\",r5(np.sum(HDweight)) )\n",
    "print(\"I am assuming we already read in a 'tractPopFile' of Census vtd geoms & pops with a GEOID20 column\")\n",
    "censusGEOID20 = tractPopFile['GEOID20']\n",
    "miniHDdf = pd.DataFrame( {\"GEOID20\":censusGEOID20} )\n",
    "vestNo = [v for v in range(nVTDs)]\n",
    "print(\"translating from HD order of precinct rows to VEST order\")\n",
    "miniVestDF = pd.DataFrame( {\"GEOID20\":mergedDF['GEOID20'], \"vestNo\":vestNo} )\n",
    "mappingDF = pd.merge(miniHDdf,miniVestDF,on=\"GEOID20\")\n",
    "vestID = mappingDF['vestNo']  #this maps each named unit in a HDVL to the correct vestNo row with voting data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "540c6d1d-7728-48bf-90f0-f124b25ac7c2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sanity check - Dem-leaning vtds for year 2020\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"sanity check - Dem-leaning vtds for year\",years[0])  #for MA, do GOP-leaning.  Other states, use Dem-leaning\n",
    "for v in range(nVTDs):\n",
    "    plotPoly(vtdGeom[v],0.2)\n",
    "    if DemVotes[0][vestID[v]] > RepVotes[0][vestID[v]]:\n",
    "        plt.text(vtdGeom[v].centroid.x, vtdGeom[v].centroid.y, \"D\", color = \"blue\",fontsize=6)\n",
    "        #plotCenter(\"d\",vtdGeom[v],6)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "56ed7e9d-1400-4848-892e-737555552d58",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, let's compute the ensemble average vote margin (GOP -  Dem total votes) for 2020 vs. true statewide result\n",
      "working on drawn district no 0\n",
      "working on drawn district no 1000\n",
      "working on drawn district no 2000\n",
      "working on drawn district no 3000\n",
      "working on drawn district no 4000\n",
      "working on drawn district no 5000\n",
      "working on drawn district no 6000\n",
      "here is the table of Dem and Rep votes, vote margin for true 2020 vs. ensemble\n",
      "true 2020: 2607921 1882732 -725189\n",
      "ensemble : 2610415 1883751 -726663\n",
      "the true and ensemble state GOP leans are 0.41926 0.41915482773204477\n"
     ]
    }
   ],
   "source": [
    "print(\"Now, let's compute the ensemble average vote margin (GOP -  Dem total votes) for 2020 vs. true statewide result\")\n",
    "nDrawnDistricts = len(HDweight)  #now including cut districts\n",
    "nMapDistricts = nCutDistricts + nDistricts\n",
    "nEnsembleDems, nEnsembleReps = [0.]*nYears, [0.]*nYears\n",
    "y=0\n",
    "for t in range(nDrawnDistricts):\n",
    "    if t%1000 == 0:\n",
    "        print(\"working on drawn district no\",t)\n",
    "    nEnsembleDems[y] += nMapDistricts* HDweight[t] * ( np.sum([DemVotes[y][vestID[v]] for v in HDvtdList[t] ])\n",
    "                                               + np.sum([DemVotes[y][vestID[v]] * splitTractUse[t][i] for i,v in enumerate(splitTractNo[t]) ])  )\n",
    "    nEnsembleReps[y] += nMapDistricts* HDweight[t] * ( np.sum([RepVotes[y][vestID[v]] for v in HDvtdList[t] ])\n",
    "                                               + np.sum([RepVotes[y][vestID[v]] * splitTractUse[t][i] for i,v in enumerate(splitTractNo[t]) ])  )\n",
    "\n",
    "print(\"here is the table of Dem and Rep votes, vote margin for true 2020 vs. ensemble\")\n",
    "print(\"true 2020:\",int(vestDems[y]),int(vestReps[y]),              int(vestReps[y] - vestDems[y]) )\n",
    "print(\"ensemble :\",int(nEnsembleDems[y]),int(nEnsembleReps[y]),    int(nEnsembleReps[y] - nEnsembleDems[y]) )\n",
    "print(\"the true and ensemble state GOP leans are\",r5(vestReps[y]/(vestReps[y]+vestDems[y])),\n",
    "      nEnsembleReps[y]/(nEnsembleReps[y]+nEnsembleDems[y]) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "5c607c63-df0d-4334-8131-368c090c76d2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "total drawn districts, HD-drawn, map districts 6361 6361 12\n"
     ]
    }
   ],
   "source": [
    "print(\"total drawn districts, HD-drawn, map districts\",nDrawnDistricts,nHDs, nMapDistricts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bb0d0d12-6bf4-4d5f-9236-fa8735393e98",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
